Multiple Objectives

In previous works the features and a complete for- mulation for circuit-switched networks of a multiple objective dynamic routing method (MODR) of periodic state dependent routing type were presented. The aim of the model is to resolve a very complex network bi-objective dynamic routing prob- lem, by recurring to a heuristic for synchronous path selec- tion enabling to obtain a good compromise solution in terms of two network performance measures. In this paper we present a study on the performance of variants of the MODR heuristic of synchronous path selection by using relaxations of the val- ues previously calculated for the two network objective func- tions. This study permitted the development of an improved version of the initial heuristic. Also a comparison of the ana- lytical values of the network objective functions obtained with selected variants of the initial heuristic with the corresponding results from a known reference method, the real time network routing (RTNR) metho...

This work presents a procedure for finding the reliability-based optimum design of cable stayed bridges. The minimization problem is stated as the minimization of stresses, displacements, reliability and bridge cost. A finiteelement approach is used for structural analysis. It includes a direct analytic sensitivity analysis module, which provides the structural behaviour responses to changes in the design variables. An equivalent multicriteria approach is used to solve the non-differentiable, non-linear optimization problem, turning the original problem into the sequential minimization of unconstrained convex scalar functions, from which a Pareto optimum is obtained. Examples are given illustrating the procedure.

This paper investigates the computation of transient-optimal policies in discrete dynamic programming. The model is quite generah it may contain transient as well as nontransient policies, and the transition matrices are not necessarily substochastic. A functional equation for the so-called transient-value-vector is derived and the concept of superharmonicity is introduced. This concept provides the linear program to compute the transientvalue-vector and a transient-optimal policy. We also discuss the elimination of suboptimal actions, the solution of problems with additional constraints, and the computation of an efficient policy for a multiple objective dynamic programming problem,

Emek et al. presented a model of probabilistic single-item second price auctions where an auctioneer who is informed about the type of an item for sale, broadcasts a signal about this type to uninformed bidders. They proved that finding the optimal (for the purpose of generating revenue) pure signaling scheme is strongly NP-hard. In contrast, we prove that finding the optimal mixed signaling scheme can be done in polynomial time using linear programming. For the proof, we show that the problem is strongly related to a problem of optimally bundling divisible goods for auctioning. We also prove that a mixed signaling scheme can in some cases generate twice as much revenue as the best pure signaling scheme and we prove a generally applicable lower bound on the revenue generated by the best mixed signaling scheme.

Traditionally, simulation has been used by project managers in optimising decision making. However, current simulation packages only include simulation optimisation which considers a single objective (or multiple objectives combined into a single fitness function). This paper aims to describe an approach that consists of using multiobjective optimisation techniques via simulation in order to help software project managers find the best values for initial team size and schedule estimates for a given project so that cost, time and productivity are optimised. Using a System Dynamics (SD) simulation model of a software project, the sensitivity of the output variables regarding productivity, cost and schedule using different initial team size and schedule estimations is determined. The generated data is combined with a well-known multiobjective optimisation algorithm, NSGA-II, to find optimal solutions for the output variables. The NSGA-II algorithm was able to quickly converge to a set of optimal solutions composed of multiple and conflicting variables from a medium size software project simulation model. Multiobjective optimisation and SD simulation modeling are complementary techniques that can generate the Pareto front needed by project managers for decision making. Furthermore, visual representations of such solutions are intuitive and can help project managers in their decision making process.

Current work in planning with preferences assume that the user's preference models are completely specified and aim to search for a single solution plan. In many real-world planning scenarios, however, the user probably cannot provide any information about her desired plans, or in some cases can only express partial preferences. In such situations, the planner has to present not only one but a set of plans to the user, with the hope that some of them are similar to the plan she prefers. We first propose the usage of different measures to capture quality of plan sets that are suitable for such scenarios: domain-independent distance measures defined based on plan elements (actions, states, causal links) if no knowledge of the user's preferences is given, and the Integrated Convex Preference measure in case the user's partial preference is provided. We then investigate various heuristic approaches to find set of plans according to these measures, and present empirical results demonstrating the promise of our approach. 1

We present a case study of artificial intelligence techniques applied to the control of production printing equipment. Like many other real-world applications, this complex domain requires high-speed autonomous decision-making and robust continual operation. To our knowledge, this work represents the first successful industrial application of embedded domain-independent temporal planning. Our system handles execution failures and multi-objective preferences. At its heart is an on-line algorithm that combines techniques from state-space planning and partial-order scheduling. We suggest that this general architecture may prove useful in other applications as more intelligent systems operate in continual, on-line settings. Our system has been used to drive several commercial prototypes and has enabled a new product architecture for our industrial partner. When compared with state-of-the-art off-line planners, our system is hundreds of times faster and often finds better plans. Our expe...

Simultaneous analysis of relationships between multiple artifact classes is required for characterization of many types of activity areas. This paper illustrates improved forms of multivariate visualization, spatial analysis and integration of experimental results that are possible with GIS based photomapping. Techniques are demonstrated through analysis of a hearth associated artifact scatter exposed during excavations of a Late Archaic pithouse at Jiskairumoko, Peru. A multivariate density raster is created and additive color visualization is used for simultaneous display of three artifact distributions. Performing unconstrained clustering in a GIS, space is classified by simultaneous relative density relationships between multiple object types.

Established in 2006, the IEEE Robotics and Automation Society (RAS) Conference Editorial Board (CEB) is responsible for handling the review process for the IEEE International Conference on Robotics and Automation. The structure of the CEB is analogous to the structure of a Transactions Editorial Board. The CEB consists of an Editor-in-Chief, nine Editors and approximately 135 Associate Editors. The Editors are responsible for supervising the assignment of papers to Associate Editors. The Associate Editors are responsible for acquiring two reviews for each paper that is submitted to the conference. These reviews are used by the conference Program Committee as a basis for final decisions. In some cases, an Associate Editor may recommend that a submission be rejected without review. In this case, if the supervising Editor agrees, the paper will be rejected without being sent out for review. The ultimate responsibility for the conference content, acceptance rate, invited sessions, etc. rests with the Program Committee. The purpose of the CEB is merely to ensure a high quality, robust, reliable and consistent review process from year to year.

In the object-oriented paradigm, objects are instances of the conceptual entities that describe their structure and behavior i.e, the classes. Recent applications of object-oriented programming languages and databases in areas like engineering design and genetics have demonstrated the limits of this assumption. Object instances cannot always conform to [heir class definitions. They may evolve during the application lifetime. Further, a class may be only one specific object representation among several others required by the users. This paper relaxes some constraints usually associated with instantiation mechanisms. An object instance is no longer considered as a perfect representative of a specific class. [t ctin bear distortions with its class definition. This is called here tlexible instantiation. An instance can also belong simultaneously to different classes. These classes need not be related by any direct or indirect specialization relationship, "l'his is called here multiple instantiation, II is shown how classifiuauon mechanisms complement adequatly multiple instantiation. The characteristics of such LI clitssitication mechanism are described. It is implemented for tin object-based knowledge representation model called SHOOD. 'I RIMAG is a research consortium involving INRIA, CNRS, lNPG, UJF and ENSL.

It is essential to study and optimize multiple objective functions such as binder system design, feedstock, part geometry, mold design, and processing conditions in order to develop a successful powder injection molding process. A powder with different combinations of binder systems and a binder system with different combinations of powder systems were investigated with a combined experimental and simulation study. First, an experimental rheological study was performed to evaluate the influence of the powder/binder combinations on the rheological behavior and thermal stability of carbonyl iron and stainless steel powder injection molding (PIM) feedstocks. Second, based on the characterization of the feedstock, the simulation study revealed that the pressure-related parameters such as wall shear stress, injection pressure, and clamping force were mainly dependent on the binder system and not much on the powder characteristics, in the range of particle attributes studied. Third, to the temperature-related parameters such as melt front temperature difference and cooling time, binder selection is more critical than powder selection. Fourth, for the velocity-related parameter, maximum shear rate, the selection of both powder and binder system is critical in control. It is demonstrated that the simulation study is essential in the development stage for successful PIM.

Abstract:-Machine Vision for industrial applications requires simple-to-use and robust solutions. Usually industrial machine vision solutions are reduced to a simple 2D application, for which algorithm robustness has already been fully demonstrated, and ...

It is shown that the use of an external archive, purely for storage purposes, can bring substantial benefits in multi-objective optimization. A new scheme for archive management for the above purpose is described. The new scheme is combined with the NSGA-II algorithm for solving two multi-objective optimization problems, and it is demonstrated that this combination gives significantly improved sets of Pareto-optimal solutions. The additional computational effort because of the external archive is found to be insignificant when the objective functions are expensive to evaluate.

This article presents a novel multi-objective economic load dispatch solution with the bee colony optimization method. The purposes of this research are to find the lowest total power generation cost and the lowest total power loss at the transmission line. A swarm optimization method was used to consider the non-smooth fuel cost function characteristics of the generator. The constraints of economic load dispatch include the cost function, the limitations of generator operation, power losses, and load demand. The suggested approach evaluates an IEEE 5, 26, and 118 bus system with 3, 6, and 15 generating units at 300, 1,263, and 2,630 megawatt (MW) and uses a simulation running on the MATLAB software to confirm its effectiveness. The outcomes of the simulation are compared with those of the exchange market algorithm, the cuckoo search algorithm, the bat algorithm, the hybrid bee colony optimization, the multi-bee colony optimization, the decentralized approach, the differential evolution, the social spider optimization, and the grey wolf optimization. It demonstrates that the suggested approach may provide a better-quality result faster than the traditional approach.

Lazarsfeld and the economist Oskar Morgenstern -with the financial support from the Ford Foundation, the Austrian Federal Ministry of Education and the City of Vienna, the Institute for Advanced Studies (IHS) is the first institution for postgraduate education and research in economics and the social sciences in Austria. The Economics Series presents research done at the Department of Economics and Finance and aims to share "work in progress" in a timely way before formal publication. As usual, authors bear full responsibility for the content of their contributions. Das Institut für Höhere Studien (IHS) wurde im Jahr 1963 von zwei prominenten Exilösterreicherndem Soziologen Paul F. Lazarsfeld und dem Ökonomen Oskar Morgenstern -mit Hilfe der Ford-Stiftung, des Österreichischen Bundesministeriums für Unterricht und der Stadt Wien gegründet und ist somit die erste nachuniversitäre Lehr-und Forschungsstätte für die Sozial-und Wirtschaftswissenschaften in Österreich. Die Reihe Ökonomie bietet Einblick in die Forschungsarbeit der Abteilung für Ökonomie und Finanzwirtschaft und verfolgt das Ziel, abteilungsinterne Diskussionsbeiträge einer breiteren fachinternen Öffentlichkeit zugänglich zu machen. Die inhaltliche Verantwortung für die veröffentlichten Beiträge liegt bei den Autoren und Autorinnen.

Earthquakes have destroyed the economy and killed many people in many countries. Emergency response actions immediately after an earthquake significantly reduce economic losses and save lives, so accurate earthquake damage predictions are needed. This research looks at how machine learning (ML) techniques are used to predict damage from earthquakes. The ML algorithms used are k-nearest neighbors (KNN), decision tree (DT), random forest (RF), and Naïve Bayes (NB). Feature selection is necessary, it needs to select the most relevant features from big data. One of the most commonly used algorithms to optimize ML is particle swarm optimization (PSO). PSO is also suitable for feature selection. This research compares various of PSO. Based on research, the RF algorithm with Phasor PSO has the highest fitness score. This process succeeded in reducing features from 38 features to 14 features. Based on the process after feature selection, it was found that the KNN, DT, and RF algorithms had improved. RF obtained the best accuracy, namely 72.989%. The processing time in DT, RF, and NB is faster than before. In conclusion, the ML algorithm can be combined with PSO feature selection to create a classification model that provides better performance than without feature selection.

co-rotating structure, was too large to fit into any available air-freight carrier. This large item was therefore securely packed and made the slightly more perilous, but more leisurely, journey on the open deck of a container ship (Figure ). Fortunately both cargoes arrived without damage, more or less at the same time, at the port in Antofagasta. KMOS then made the final leg of the journey by road to the new integration hall at the Paranal Observatory. KMOS was fully re-assembled and recalibrated in the integration hall over an eight-week period in September-November 2012 by a dedicated team of technical experts from the UK and German consortium partners, working closely with ESO personnel. After an extensive set of verification tests, the instrument was then taken up the final stretch of the mountain road at walking pace (Figure , left), before being installed on the Nasmyth platform of VLT Unit Telescope 1 (Antu). Because of the size of the CACOR (about four metres high), this item had to be lifted directly

We present an active learning approach for visual multiple object class recognition, using a Conditional Random Field (CRF) formulation. We name our graphical model 'collaborative', because it infers class posteriors in instances of occlusion and missing information by assessing the joint appearance and geometric assortment of neighboring sites. The model can handle scenes containing multiple classes and multiple objects inherently while using the confidence of its predictions to enforce label uniformity in areas where evidence supports similarity. Our method uses classification uncertainty to dynamically select new training samples to retrain the discriminative classifiers used in the CRF. We demonstrate the performance of our approach using cluttered scenes containing multiple objects and multiple class instances.

The drainage system is an infrastructure that requires systematic planning of construction which can function properly to reduce the risk of flooding. Flooding occurs due to the rapid development resulting in lack of permeable surfaces. This will lead to increase the surface runoff, where the flow velocity and flow discharge also will be increased. Therefore, grassed swale is one of the sustainable drainage systems that can be applied to solve this problem. This study aims to identify the effectiveness of the grassed swale drainage system at Universiti Tun Hussein Onn Malaysia (UTHM), to determine the hydraulic characteristics and the effectiveness of vegetation used in the swale drainage system. Through this approach, the solution of past studies, related journals, and Manual Saliran Mesra Alam (MSMA) [1] are used as a reference for this study. Data collection was conducted on grassed swale with total length 60 meters. To obtain an accurate data, measurements of flow velocity have ...

La nouvelle révolution de la connaissance et de l'immatériel plonge immanquablement l'entreprise dans une ère de remise en cause profonde des modes conventionnels de gestion. Le Knowledge Management comme mode prépondérant émerge et consacre son insertion dans l'économie de la connaissance. Dans ce travail, nous tenterons d' apporter un meilleur éclairage de ce concept, et à en saisir les implications sur l'organisation de l'entreprise. Nous examinerons en second lieu quelques expériences de son adoption par l'entreprise algérienne largement insérée dans un contexte d'ouverture croissante. Des illustrations de travaux publiés sont utilisés. Quelques perspectives sont tracées et quelques recommandations faites.

As technologies evolve, there have been high demands for the three-dimensional (3D) shape measurement techniques to posses the following combined technical features: high accuracy, fast speed, easy implementation, capability of measuring multiple objects as well as measuring complex shapes. Generally, the existing techniques can satisfy some of the requirements, but not all of them. This paper presents four practical considerations in fringe projection profilometry (FPP) based 3D shape measurements, along with simple but robust solutions, including gamma correction of digital projection, arbitrary setup of system components, phase unwrapping with multi-frequency fringes, and system calibration with a least-squares inverse approach. The validity and practicability of the FPPbased 3D shape measurement technique using the four corresponding technical approaches have been verified by experiments. The presented technique is capable of satisfying the various critical demands in enormous scientific and engineering applications.

In the identification of reserve networks in fragmented landscapes with limited species-specific data at hand, one approach is to use selection criteria, such as patch size, to rank the habitat patches' conservation value and evaluate reserve-network alternatives. These criteria are assumed to be reasonable surrogates for the true network objectives. Caution is warranted, however, because the relationships between the selection criteria and the reserve-network objectives may be inconsistent. Conflicts are also likely to arise because no single reserve network will be optimal with respect to multiple objectives (or selection criteria) simultaneously. Instead, reserve planners must compromise between conflicting demands. We field tested the relationships between a variety of selection criteria and the objectives of a reserve network for the sandplain natural communities on Martha's Vineyard Island, Massachusetts (U.S.A.). Selection criteria that correlated with the reserve-network objectives were used in a multi-objective integer program to identify the 10-patch reserve networks that were optimal with each objective independently and those that offered optimal tradeoffs between the reserve-network objectives. From these 10-patch networks, one can select a final reserve network that provides the preferred compromise between the objectives. Resumen: La utilización de criterios de selección, como el tamaño de parche, para clasificar el valor de conservación de los parches de hábitat y evaluar redes de reservas alternativas es un método para identificar redes de reservas en paisajes fragmentados con datos especie-específicos limitados,. Se asume que estos criterios son sustitutos razonables de los verdaderos objetivos de la red. Sin embargo, se requiere cuidado porque las relaciones entre los criterios de selección y los objetivos de la red de reservas pueden ser inconsistentes. Es probable que surjan conflictos porque ninguna red de reservas será óptima con respecto a objetivos (o criterios de selección) múltiples simultáneamente. Más bien, los planificadores de reservas deben transigir entre demandas conflictivas. Probamos las relaciones entre una variedad de criterios de selección y los objetivos de una red de reservas para comunidades arenícolas naturales en la Isla Martha's Vineyard, Massachussets (E.U.A.). Los criterios de selección que se correlacionaron con los objetivos de la red de reservas fueron utilizados en un programa multi-objetivo integral para identificar las 10 redes de reservas de fragmentos óptimas con cada objetivo independientemente y las que ofrecían compensaciones óptimas entre los objetivos de la red de reservas. De estas 10 redes de reservas de fragmentos, se puede seleccionar una red de reservas final que proporcione el compromiso preferido entre los objetivos.

Current work in planning with preferences assume that the user's preference models are completely specified and aim to search for a single solution plan. In many real-world planning scenarios, however, the user probably cannot provide any information about her desired plans, or in some cases can only express partial preferences. In such situations, the planner has to present not only one but a set of plans to the user, with the hope that some of them are similar to the plan she prefers. We first propose the usage of different measures to capture quality of plan sets that are suitable for such scenarios: domain-independent distance measures defined based on plan elements (actions, states, causal links) if no knowledge of the user's preferences is given, and the Integrated Convex Preference measure in case the user's partial preference is provided. We then investigate various heuristic approaches to find set of plans according to these measures, and present empirical results demonstrating the promise of our approach. 1

The detection of communities is an important problem in social network analysis, which has applications in various domains like sociology, biology, computer science, and marketing. In this context, genetic algorithms have proven to be effective in detecting communities by optimizing the modularity score of the network. The proposed work in this research paper uses an elitism-based genetic algorithm with some modified crossover and mutation techniques to detect communities in social networks. The proposed methodology incorporates the concepts of elitism, N-point crossover, and inverse mutation to enhance the effectiveness of genetic algorithms in solving optimization problems. The idea introduced in this article significantly extends the current understanding of optimization and evolutionary algorithms. We present an advanced methodology that leverages various genetic operators to improve the performance of a genetic algorithm in solving community detection problems in complex networks. Numerous research papers have extensively showcased the practicality of evolutionary and swarm-based algorithms in addressing real-world problems across diverse domains like viral marketing, link prediction, influence maximization, political polarization, etc. Hybridizing these algorithms with other optimization techniques has improved the performance and convergence speed, leading to enhanced optimization outcomes.

A multi-objective particle swarm optimization (MOPSO) approach for multi-objective economic load dispatch problem in power system is presented in this paper. The economic load dispatch problem is a non-linear constrained multi-objective optimization problem. The proposed MOPSO approach handles the problem as a multi-objective problem with competing and non-commensurable fuel cost, emission and system loss objectives and has a diversity-preserving mechanism using an external memory (call "repository") and a geographically-based approach to find widely different Pareto-optimal solutions. In addition, fuzzy set theory is employed to extract the best compromise solution. Several optimization runs of the proposed MOPSO approach were carried out on the standard IEEE 30-bus test system. The results revealed the capabilities of the proposed MOPSO approach to generate well-distributed Pareto-optimal non-dominated solutions of multi-objective economic load dispatch. Comparison with Multi-objective Evolutionary Algorithm (MOEA) showed the superiority of the proposed MOPSO approach and confirmed its potential for solving multi-objective economic load dispatch.

Many safety related and critical systems warn of potentially dangerous events; for example, the Short Term Conflict Alert (STCA) system warns of airspace infractions between aircraft. Although installed with current technology such critical systems may become out of date due to changes in the circumstances in which they function, operational procedures and the regulatory environment. Current practice is to 'tune' by hand the many parameters governing the system in order to optimise the operating point in terms of the true positive and false positive rates, which are frequently associated with highly imbalanced costs. In this paper we cast the tuning of critical systems as a multi-objective optimisation problem. We show how a region of the optimal receiver operating characteristic (ROC) curve may be obtained, permitting the system operators to select the operating point. We apply this methodology to the STCA system, using a multi-objective (1+1)-evolution strategy, showing that we can improve upon the current hand-tuned operating point, as well as providing the salient ROC curve describing the true positive versus false positive trade-off. We also provide results for three-objective optimisation of the alert response time in addition to the true and false positive rates. Additionally, we illustrate the use of bootstrapping for representing evaluation uncertainty on estimated Pareto fronts, where the evaluation of a system is based upon a finite set of representative data.

The Receiver Operating Characteristic (ROC) has become a standard tool for the analysis and comparison of classifiers when the costs of misclassification are unknown. There has been relatively little work, however, examining ROC for more than two classes. Here we discuss and present an extension to the standard twoclass ROC for multi-class problems. We define the ROC surface for the Q-class problem in terms of a multi-objective optimisation problem in which the goal is to simultaneously minimise the Q(Q -1) misclassification rates, when the misclassification costs and parameters governing the classifier's behaviour are unknown. We present an evolutionary algorithm to locate the Pareto front-the optimal trade-off surface between misclassifications of different types. The use of the Pareto optimal surface to compare classifiers is discussed and we present a straightforward multi-class analogue of the Gini coefficient. The performance of the evolutionary algorithm is illustrated on a synthetic three class problem, for both k-nearest neighbour and multi-layer perceptron classifiers.

Solving the mystery of the nature of dark energy is the most important problem in cosmology today. JEDI (Joint Efficient Dark-energy Investigation) is a candidate implementation of the NASA-DOE Joint Dark Energy Mission (JDEM). JEDI will probe dark energy in three independent ways by measuring the expansion history of the universe: (1) using type Ia supernovae as cosmological standard candles over a range of distances, (2) using baryon oscillations as a cosmological standard ruler over a range of cosmic epochs, (3) mapping the weak gravitational lensing distortion by foreground galaxies of the images of background galaxies at different distances. JEDI will unravel the nature of dark energy with accuracy and precision. JEDI is a 2m-class space telescope with the unique ability of simultaneous wide-field imaging (0.8-4.2 µm in five bands) and multi-slit spectroscopy (0.8-3.2 µm) with a field of view of 1 square degree. What makes JEDI efficient is its ability to simultaneously obtain high signal-to-noise ratio, moderate resolution slit spectra for all supernovae and ∼ 5000 galaxies in its wide field of view, and to combine imaging and spectroscopy so that the appropriate balance of time is devoted to each. Another unique feature of JEDI is that it will be cold. This extends the wavelength range just past 4 µm which is critical in limiting systematics caused by dust extinction. JEDI requires 64 2048×2048 HgCdTe detectors, and 8 175×384 arrays of microshutters as the spectrograph slit mask (both already developed for the JWST). JEDI will orbit in L2, with sunshields to achieve passive cooling. JEDI will measure the cosmic expansion history H(z) as a free function to < ∼ 2% accuracy in redshift bins of 0.2-0.3. Assuming a flat universe and σ(Ω m ) = 0.01 (0.03), JEDI could measure a departure from a vanilla ΛCDM model (w 0 = -1, w ′ = 0) with σ(w 0 ) = 0.013 (0.031) and σ(w ′ ) = 0.046 (0.063). JEDI will obtain the well-sampled lightcurves in Z, J, H, K, L bands and spectra of ∼ 14,000 type Ia supernovae with redshifts ranging from 0 to 1.7; the redshifts of ∼ 10-100 million galaxies to H ∼ 23 and z ∼ 4 over 1000-10,000 square degrees; and measurements of the shapes of galaxies over 1000-10,000 square degrees in Z, J, H, K, L for > ∼ 10 9 galaxies to H ∼ 25.

Scent research has focused primarily on the effects of ambient scent on consumer evaluations. We focus instead on the effects of product scent on consumer memories. For instance, if a pencil or a facial tissue is imbued with scent (vs. not), recall for the brand's other attributes increases significantly-with the effects lasting as much as 2 weeks after exposure. We also find that product scent is more effective than ambient scent at enhancing memory for product information. We suggest that this may be because, with product (ambient) scent, scent-related associations are focused on a single object (are diffused across multiple objects) in the environment. In support, we find that the memory effects are driven by the number of product/scent-related associations stored in long-term memory. The results suggest that, although ambient scent has received the bulk of attention from researchers and managers in recent years, greater focus on product scent is warranted. T he actions of firms in recent years suggest that imbuing products with scents can enhance brand equity. Firms have sought scent-based trademarks for products such as sewing thread (Brookman 1999), automobile tires (Carter 1995), and tennis balls . Are such trademark protection efforts worthwhile? We attempt to answer this question by exploring the effect of product scent on consumers' ability to remember product information over time. To date, consumer research on scent has focused primarily on the effects of scent on product evaluation (Bone

The design of efficient communication networks is a challenging task for modern vehicle development. Due to novel technologies and new degrees of freedom in network design, the decision on a bus topology has a severe impact on the overall system cost and performance. In this work, we propose a topology and routing optimization using Evolutionary Algorithms and problem-specific encoding. Our contribution includes a guided topology mutation operator which outperforms standard random mutation. Further, we propose two routing operators for usage during the optimization process and compare their effectiveness on a network application taken from a series vehicle.

We construct a family of retaliatory equilibria for the Japanese ascending auction for multiple objects, thus showing that while it is immune to many of the tacitly collusive equilibria studied in the literature, it is not entirely immune when some bidders are commonly known to be interested in a specific object.

Numerous routing schemes have been reported to improve network performance over the years. Multi-path routing belongs to one of them and MPLS is an excellent platform for such routing. In this paper, the Shortest Distance Path Based Simulated Annealing (SDPSA) algorithm for finding optimal bandwidth reservation solutions for multi-path routing is developed to improve network performances. The algorithm, which employs the annealing method, is based on previous solutions to find the current sub-optimal solution for multi-path routing. Multiple objectives including balancing traffic load and minimizing network resource consumption are taken into consideration. Finally, the proposed algorithm is applied to a randomly generated network and the NSFNET network. The performance values are compared to a well-known multi-path routing algorithm-HSTwp. The simulation and comparison results show that the proposed SDPSA algorithm is feasible and efficient for the optimization of multi-path IP routing.

The optimization of composite materials such as concrete deals with the problem of selecting the values of several variables which determine composition, compressive stress, workability and cost etc. This study presents multi-objective optimization (MOO) of high-strength concretes (HSCs). One of the main problems in the optimization of HSCs is to obtain mathematical equations that represents concrete characteristic in terms of its constitutions. In order to solve this problem, a two step approach is used in this study. In the first step, the prediction of HSCs parameters is performed by using regression analysis, neural networks and Gen Expression Programming (GEP). The output of the first step is the equations that can be used to predict HSCs properties (i.e. compressive stress, cost and workability). In order to derive these equations the data set which contains many different mix proportions of HSCs is gathered from the literature. In the second step, a MOO model is developed by making use of the equations developed in the first step. The resulting MOO model is solved by using a Genetic Algorithm (GA). GA employs weighted and hierarchical method in order to handle multiple objectives. The performances of the prediction and optimization methods are also compared in the paper.

As technologies evolve, there have been high demands for the three-dimensional (3D) shape measurement techniques to posses the following combined technical features: high accuracy, fast speed, easy implementation, capability of measuring multiple objects as well as measuring complex shapes. Generally, the existing techniques can satisfy some of the requirements, but not all of them. This paper presents four practical considerations in fringe projection profilometry (FPP) based 3D shape measurements, along with simple but robust solutions, including gamma correction of digital projection, arbitrary setup of system components, phase unwrapping with multi-frequency fringes, and system calibration with a least-squares inverse approach. The validity and practicability of the FPPbased 3D shape measurement technique using the four corresponding technical approaches have been verified by experiments. The presented technique is capable of satisfying the various critical demands in enormous scientific and engineering applications.

We investigate on designing agents facing multiple objectives simultaneously, that creates difficult situations, even if each objective is of low complexity. The present paper builds on an existing action selection process based on basic behaviors (resulting in a modular architecture) and proposes an algorithm for automatically selecting and learning the required basic behaviors through an incremental Reinforcement Learning approach. This leads to a very autonomous architecture, as the hand-coding is here reduced to its minimum.

This paper presents a real-time auditory and visual tracking of multiple objects for humanoid under real-world environments. Real-time processing is crucial for sensorimotor tasks in tracking, and multiple-object tracking is crucial for real-world applications. Multiple sound source tracking needs perception of a mixture of sounds and cancellation of motor noises caused by body movements. However its real-time processing has not been reported yet. Real-time tracking is attained by fusing information obtained by sound source localization, multiple face recognition, speaker tracking, focus of attention control, and motor control. Auditory streams with sound source direction are extracted by active audition system with motor noise cancellation capability from 48 KHz sampling sounds. Visual streams with face ID and 3D-position are extracted by combining skincolor extraction, correlation-based matching, and multiple-scale image generation from a single camera. These auditory and visual streams are associated by comparing the spatial location, and associated streams are used to control focus of attention. Auditory, visual, and association processing are performed asynchronously on different PC's connected by TCP/IP network. The resulting system implemented on an upper-torso humanoid can track multiple objects with the delay of 200 msec, which is forced by visual tracking and network latency.

A probabilistic method is proposed for segmentation of multiple objects that overlap or are in close proximity to one another. A likelihood function is formulated that explicitly models overlapping object appearance. Priors on global appearance and geometry (including shape) are learned from example images. Markov chain Monte Carlo methods are used to obtain samples from a posterior distribution over model parameters from which expectations can be estimated. The method is described in detail for the problem of segmenting femur and tibia in x-ray images. The result is a probabilistic segmentation that quantifies uncertainty so that measurements such as joint space can be made with associated uncertainty.

Effective visual object recognition requires mechanisms to bind object features (e.g. color, shape and motion) while distinguishing distinct objects. Synchronously active neuronal circuits among reentrantly connected cortical areas may provide a basis for visual binding. To assess the potential of this mechanism, we have constructed a mobile brain-based device, Darwin VIII, which is guided by simulated analogues of cortical and sub-cortical areas required for visual processing, decision-making, reward and motor responses. These simulated areas are reentrantly connected and each area contains neuronal units representing both the mean activity level and the relative timing of the activity of groups of neurons. Darwin VIII learns to discriminate among multiple objects with shared visual features and associates 'target' objects with innately preferred auditory cues. We observed the co-activation of globally distributed neuronal circuits that corresponded to distinct objects in Darwin VIII's visual field. These circuits, which are constrained by a reentrant neuroanatomy and modulated by behavior and synaptic plasticity, are necessary for successful discrimination. By situating Darwin VIII in a rich real-world environment involving continual changes in the size and location of visual stimuli due to self-generated movement, and by recording its behavioral and neuronal responses in detail, we were able to show that reentrant connectivity and dynamic synchronization provide an effective mechanism for binding the features of visual objects.

Lexical choices in descriptions of the spatial world around us are affected not only by geometry, but also by variables such as situational context and the extent to which the spatial relations between the objects referred to are seen as consistent with their typical function. In a study of how people describe complex scenes with multiple objects we examined whether descriptive choices (both locally at the lexical level but also at a more global descriptive scheme level) are guided by knowledge about the spatial arrangement (functional versus non-functional doll's furniture arrangements) and by the contextual schemas evoked in the task instruction (a living room context versus a furniture showroom). Participants' choices varied both in terms of the order in which objects in the array were described (trajectory strategies) and in spatial language depending on the functionality of the array. The context of instruction had a more limited role affecting only one aspect of the spatial language used.

We present a case study of artificial intelligence techniques applied to the control of production printing equipment. Like many other real-world applications, this complex domain requires high-speed autonomous decision-making and robust continual operation. To our knowledge, this work represents the first successful industrial application of embedded domain-independent temporal planning. Our system handles execution failures and multi-objective preferences. At its heart is an on-line algorithm that combines techniques from state-space planning and partial-order scheduling. We suggest that this general architecture may prove useful in other applications as more intelligent systems operate in continual, on-line settings. Our system has been used to drive several commercial prototypes and has enabled a new product architecture for our industrial partner. When compared with state-of-the-art off-line planners, our system is hundreds of times faster and often finds better plans. Our expe...

The identification of the reasons for the existing fiscal imbalance shows that it is necessary to introduce the institutional solutions of the budgetary process. This paper aims to verify the hypothesis that the application of multi-year budgeting is a factor which increases fiscal discipline and promotes efficiency and transparency of public finance. The research presents a comparative analysis of the quality of macroeconomic forecasts for EU countries including parameters such as the real GDP growth rate, general government sector deficit to GDP ratio, public debt to GDP ratio. Information contained in the EU Stability and Convergence Programmes and in the International Budget Practices and Procedures Database published by the OECD constituted the source of data for the research.

Targets and limits for long-term management are used in fisheries advice to operationalize the way management reflects societal priorities on ecological, economic, social and institutional aspects. This study reflects on the available published literature as well as new research presented at the international ICES/Myfish symposium on targets and limits for long term fisheries management. We examine the inclusion of ecological, economic, social and institutional objectives in fisheries management, with the aim of progressing towards including all four objectives when setting management targets or limits, or both, for multispecies fisheries. The topics covered include ecological, economic, social and governance objectives in fisheries management, consistent approaches to management, uncertainty and variability, and fisheries governance. We end by identifying ten ways to more effectively include multiple objectives in setting targets and limits in ecosystem based fisheries management.

In the paper, three algorithms for the multiobjective optimization based on the strategy of a selforganized migration are compared. The first two algorithms-Weighted Sum Method and Rotated Weighted Metric Method-transform multiple objectives into a single fitness function. The third method-a novel MOSOMAcombines the principle of the non-dominated sorting of population in the objective space and the survey of the decision space of input variables based on the selforganized migration. All three algorithms are compared on the test problem with the Pareto front, which contains both convex and non-convex parts. Monitored parameters are generational distance, spread of solutions and CPU time.

This paper introduces and develops a new approach to the theory of continuous time jump Markov decision processes (CTJMDP). This approach reduces discounted CTJMDPs to discounted semi-Markov decision processes (SMDPs) and eventually to discrete-time Markov decision processes (MDPs). The reduction is based on the equivalence of strategies that change actions between jumps and the randomized strategies that change actions only at jump epochs. This holds both for one-criterion problems and for multiple-objective problems with constraints. In particular, this paper introduces the theory for multiple-objective problems with expected total discounted rewards and constraints. If a problem is feasible, there exist three types of optimal policies: (i) nonrandomized switching stationary policies, (ii) randomized stationary policies for the CTJMDP, and (iii) randomized stationary policies for the corresponding SMDP with exponentially distributed sojourn times, and these policies can be impleme...

A linguistic-based meta-heuristic modeling and solution approach for solving the¯exible job shop scheduling problem (FJSSP) is presented in this study. FJSSP is an extension of the classical jobshop scheduling problem. The problem de®nition is to assign each operation to a machine out of a set of capable machines (the routing problem) and to order the operations on the machines (the sequencing problem), such that prede®ned performance measures are optimized. In this research, the scope of the problem is widened by taking into account the alternative process plans for each part (process plan selection problem). Probabilistic selection of alternative process plans and machines are also considered. The FJSSP is presented as a grammar and the productions in the grammar are de®ned as controls (Baykasog AElu, 2002). Using these controls and Gif¯er and Thompson's (1960) priority rule-based heuristic along with the multiple objective tabu search algorithm of Baykasog AElu et al. (1999) FJSSP is solved. This novel approach simpli®es the modeling process of the FJSSP and enables usage of existing job shop scheduling algorithms for its fast solution. Instead of scheduling job shops with in¯exible algorithms that cannot take into account the¯exibility which is available in the job shop, the present algorithm is developed which can take into account the¯exibility during scheduling. Such an approach will considerably increase the responsiveness of the job shops.

The application of multiple-objective route choice for in-vehicle route guidance systems is discussed. A bi-objective path search algorithm is presented and its use demonstrated. A concept of trip quality is introduced that is composed of two objectives: minimizing travel time and minimizing trip complexity. Trade-offs between the objectives are examined. The concept is illustrated through simulation modeling on a test network. The experiments serve to demonstrate the effects on the trip performance of pretrip routing and dynamic routing strategies under full market penetration (an idealized condition) and under varying levels of demand and trade-offs between time and complexity.

In this paper, we characterize the morphology of the disk-integrated phase 2 functions of satellites and rings around the giant planets of our Solar Sys-3 tem. We find that the shape of the phase function is accurately represented 4 by a logarithmic model (Bobrov, 1970, in Surfaces and Interiors of Planets 5 and Satellites, Academic, edited by A. Dollfus). For practical purposes, we also 6 parametrize the phase curves by a linear-exponential model (Kaasalainen et al., 7