IEBIS

Currently, business modelling is an art, instead of a science, as no scientific method for business modelling exists. This, and the lack of using business models altogether, causes many projects to end after the pilot stage, unable to fulfil their apparent promise. We propose a structured method to create "as-is" business models in a repeatable manner. The method consists of the following steps: identify the involved roles, recognize relations among roles, specify the main activities, and quantify using realistic estimates of the model. The resulting business model is suitable for analysis of the current situation. This is the basis for further predictions, for example business cases, scenarios, and alternative innovations. We offer two extra steps to develop these innovations and analyse alternatives. Using them may enable successful projects to be implemented, instead of ending on a shelf after the pilot stage.

We address the field of internal logistics, embodied in Automated Material Handling Systems (AMHSs), which are complex installations employed in sectors such as Baggage Handling, Physical Distribution, and Parcel & Postal. We work on designing an integral planning and real-time control architecture, and a set of generic algorithms for AMHSs. Planning and control of these systems need to be robust, and to yield close-to-optimal system performance. Currently, planning and control of AMHSs is highly customized and project specific. This has important drawbacks for at least two reasons. From a customer point of view, the environment and user requirements of systems may vary over time, yielding the need for adaptation of the planning and control procedures. From a systems' deliverer point of view, an overall planning and control architecture that optimally exploits synergies between the different market sectors, and at the same time is flexible with respect to changing business parameters and objectives is highly valuable. An integral planning and control architecture should clearly describe the hierarchical framework of decisions to be taken at various levels, as well as the required information for decisions at each level, e.g., from overall workload planning to local traffic control. In this research, we identify synergies among the different sectors, and exploit these synergies to decompose AMHSs into functional modules that represent generic building blocks. Thereafter, we develop generic algorithms that achieve (near) optimal performance of the modules. As an example, we present a functional module from the Parcel & Postal sector. In this module, we study merge configurations of conveyor systems, and develop a generic priority-based real-time scheduling algorithm.

Predicting the amount of money that can be claimed is critical to the effective running of an Hospital. In this paper we describe a case study of a Dutch Hospital where we use process mining to predict the cash flow of the Hospital. In order to predict the cost of a treatment, we use different data mining techniques to predict the sequence of treatments administered, the duration and the final "care product" or diagnosis of the patient. While performing the data analysis we encountered three specific kinds of noise that we call sequence noise, human noise and duration noise. Studies in the past have discussed ways to reduce the noise in process data. However, it is not very clear what effect the noise has to different kinds of process analysis. In this paper we describe the combined effect of sequence noise, human noise and duration noise on the analysis of process data, by comparing the performance of several mining techniques on the data.

Augmented reality has been a research area for decades. However, there has not been a real breakthrough for commercial applications. Augmented reality still seems like the technology of the near feature. A research carried out to investigate success factors for Augmented reality business models. The reseach is divided into three parts, the business aspect, user aspect, and technology aspect.

The research described in this paper is aimed at solving planning problems associated with a new hospital declaration methodology called DOT. With this methodology, that will become mandatory starting January 1 st 2012, hospitals will no longer be able to tell in advance how much they will receive for the care they provide. A related problem is that hospitals do not know when delivered care becomes declarable. Topicus Fincare wants to find a solution to both these problems.

Predicting the amount of money that can be claimed is critical to the effective running of an Hospital. In this paper we describe a case study of a Dutch Hospital where we use process mining to predict the cash flow of the Hospital. In order to predict the cost of a treatment, we use different data mining techniques to predict the sequence of treatments administered, the duration and the final ”care product” or diagnosis of the patient. While performing the data analysis we encountered three specific kinds of noise that we call sequence noise, human noise and duration noise. Studies in the past have discussed ways to reduce the noise in process data. However, it is not very clear what effect the noise has to different kinds of process analysis. In this paper we describe the combined effect of sequence noise, human noise and duration noise on the analysis of process data, by comparing the performance of several mining techniques on the data.

Renewable energy (RE) generation is expected to become the main source of energy in Sub-Saharan Africa (SSA) over the next century. However, more often than not, the sustainability aspect of these projects is a characteristic that is not clearly defined in terms of projects implemented in SSA. The rate at which projects fail is creating a negative impact towards the full acceptance of renewable energy technologies (RETs). The aim of this paper is to comprehensively explore the reasons of failures and provide recommendations towards the sustainable management of RE projects in SSA. We accomplish this by combining findings from past literature on the failures of RE projects in SSA with an ethnographic approach and practical experience in the implementation of RE projects in Sub-Saharan Africa. We propose the following solutions: (i) transparency, (ii) ownership, (iii) shared responsibility and (iv) community involvement. We further present hermeneutic recommendations that should be taken into account by stakeholders towards implementation of any sustainable renewable energy project.

In this paper we consider a real-time, dynamic pickup and delivery problem with timewindows where orders should be assigned to one of a set of competing transportation companies. Our approach decomposes the problem into a multi-agent structure where vehicle agents are responsible for the routing and scheduling decisions and the assignment of orders to vehicles is done by using a second-price auction. Therefore the system performance will be heavily dependent on the pricing strategy of the vehicle agents. We propose a pricing strategy for vehicle agents based on dynamic programming where not only the direct cost of a job insertion is taken into account, but also its impact on future opportunities. We also propose a waiting strategy based on the same opportunity valuation. Simulation is used to evaluate the benefit of pricing opportunities compared to simple pricing strategies in different market settings. Numerical results show that the proposed approach provides high quality solutions, in terms of profits, capacity utilization and delivery reliability.

In this paper we study the real-time scheduling of time-sensitive full truckload pickup-and-delivery jobs. The problem involves the allocation of jobs to a fixed set of vehicles which might belong to different collaborating transportation agencies. A recently proposed solution methodology for this problem is the use of a multi-agent system where shipper agents offer jobs through sequential auctions and vehicle agents bid on these jobs. In this paper we consider such a system where both the vehicle agents and the shipper agents are using profit maximizing look-ahead strategies. Our main contribution is that we study the interrelation of these strategies and their impact on the system-wide logistical costs. From our simulation results, we conclude that the system-wide logistical costs (i) are always reduced by using the look-ahead strategies instead of a myopic strategy (10-20%) and (ii) the joint effect of two look-ahead strategies is larger than the effect of an individual strategy. To provide an indication of the savings that might be realized under centralized decision making, we benchmark our results against an integer programming approach. Keywords Multi-agent systems • Collaborative planning • Auctions/bidding • Transportation 1 Introduction During the last decade there has been a growing interest in collaborative logistics as a result of increasing pressure on shippers and carriers to operate more efficiently. Cooperation among transportation agencies takes place on various organizational and

This paper addresses the problem of generic planning and control of automated material handling systems (AMHSs). We build upon previous work to provide a proof of concept for generic control of AMHSs in different domains. We present a generic control architecture for AMHSs, and apply this architecture to a material flow model with storage and sorter systems. We set up our model to be applicable to AMHSs in two different industrial sectors: Baggage Handling and Distribution. We report on performance indicators and analyze how far we can control the two industries generically in terms of software implementation. To this end, we present an impressive degree of 84% commonality in the control software code. Moreover, we highlight deviations from the generic control and give insight to control procedures that deviate from the generic code. A generic architecture that optimally exploits synergy between the different market sectors may reduce design time and costs considerably for system suppliers acting in both industries, while finding a common ground to model AMHSs in these different sectors also forms a scientific challenge.

In this paper we consider a multi-agent system (MAS) for the logistics control of Automatic Guided Vehicles (AGVs) that are used in the dough making process at an industrial bakery. Here, logistics control refers to constructing robust schedules for all transportation jobs. The paper discusses how alternative MAS designs can be developed and compared using cost, frequency of messages between agents, and computation time for evaluating control rules as performance indicators. Qualitative design guidelines turn out to be insufficient to select the best agent architecture. Therefore, we also use simulation to support decision making, where we use real-life data from the bakery to evaluate several alternative designs. We find that architectures in which line agents initiate allocation of transportation jobs, and AGV agents schedule multiple jobs in advance, perform best. We conclude by discussing the benefits of our MAS systems design approach for real-life applications.

Multi-Agent systems have been studied extensively, but only a few of these systems are deployed in practice. Essential to get a system implemented is acceptance. In a distributed setting this is challenging, especially when one deals with multiple independent and competing companies. We share our experiences with the use of a real-time multi-player simulation game that we developed to illustrate a Multi-Agent system for the barge handling problem in the Port of Rotterdam. We experienced that the game has many advantages over a more passive approach, such as vocal presentations. We conclude that the game has considerably contributed to the acceptance of the illustrated Multi-Agent system.

In a recent article (Heppes and Melissen, Period. Math. Hungar. 34 (1997) 63-79), Heppes and Melissen have determined the thinnest coverings of a rectangle with up to ÿve equal circles and also for seven circles if the aspect ratio of the rectangle is either between 1 and 1:34457 : : : ; or larger than 3:43017 : : :. In this paper we extend these results. For the gap in the seven circles case we present thin coverings that we conjecture to be optimal. For six circles we determine the thinnest possible covering if the aspect ratio is larger than 3:11803 : : :. Furthermore, for six and seven circles, we give thin coverings for the remaining range of values, thereby extending our previous conjecture for the square (Melissen and Schuur, Electron. J. Combin. 3 (1996) R32). [6].

This paper deals with a new strategy for the assignment of Stock Keeping Units (SKUs) to storage locations in a warehouse, called Order Oriented Slotting (OOS). Given an empty warehouse, a set of orders to be picked and a routing policy, OOS stores the SKUs in such a way that the total time needed to pick all the orders is minimised. Unlike the Cube per Order Index (COI) slotting strategy which stores an item based on how frequently it is picked without regard to picking sequences, OOS aims to store items, that appear together in orders, close to each other. OOS can be formulated as an Integer Linear Programming model when the routing is S-shaped and when a Vertical Lift Module (VLM) is adopted. Given the computational complexity of the problem, we present several heuristics. Their performance is compared through a set of VLM test problems with different order characteristics.

We consider a key issue in hinterland container navigation in ports, such as Rotterdam and Antwerp, namely the barge handling problem: how to optimize the alignment of barge and terminal operations in a port. We make a major step in solving the barge handling problem for practical settings. Specifically, we consider restricted opening times of terminals, unbalanced networks, the presence of sea vessels, and closing times of containers. Consequently, at a terminal a barge faces time dependency in: (1) the waiting time until the start of handling and (2) the handling time itself. The concept of waiting profiles which we introduced in an earlier paper only deals with (1). To deal with (1) and (2) together we introduce a more comprehensive concept, namely that of service-time profile. To establish how well our approach works, we evaluate the performance of our distributed planning approach extensively by means of simulation. We compare our results with those based on centralized planning by using an off-line benchmark resembling it. We show that the Multi-Agent system that we introduce enables barge and terminal operators to align their operations efficiently. Hence, it can be seen as a promising solution approach for solving the barge handling problem, since it enables (competing) companies to collaborate in a competitive way.

The batching of jobs in a manufacturing system is a very common policy in many industries. The main reasons for batching are the avoidance of setups and/or facilitation of material handling. Good examples of batch-wise production systems are the ovens that are found in the aircraft industry and in the manufacture of semiconductors. These systems often consist of multiple machines of dierent types for the range and volumes of products that have to be handled. Building on earlier research in the aircraft industry, where the process of hardening synthetic aircraft parts was studied, we propose a new heuristic for the dynamic scheduling of these types of systems. Our so-called look-ahead strategy bases its decision to schedule a job on a certain machine on the availability of information on a limited number of near future arrivals. The new control strategy distinguishes itself from existing heuristics by an integrated approach that involves all machines in the scheduling decision, instead of only considering idle machines. It is shown by an extensive series of simulation experiments that the new heuristic outperforms existing heuristics for most system con®gurations. Especially in the case of complex systems, where multiple products have to be handled by non-identical machines, the new heuristic proves its value as a practical scheduling tool. Important insight is obtained with regard to the relation between the system is con®guration and its performance.

The consumer electronics (CE) industry has high turnovers and a growing demand, such as on the home entertainment segment. At the same time, it generates e-waste of the order of a dozen million tons, about one quarter of the world's total. With the purpose of improving the environmental performance of businesses, the Waste Electrical and Electronic Equipment (WEEE) Directive was put in place in Europe. Given the high competitive environment of this industry, WEEE could be a clue for competitive edge. To create an environmental and economic win-win situation, however, companies have to master reverse logistics (RL). This is particularly challenging in fast clockspeed environments, as it is the case for the CE industry. In this paper, we develop a theoretically and empirically grounded diagnostic tool for assessing a CE company's RL practices and identifying potential for RL improvement, from a business perspective. To theoretically ground the tool, we combine specific CE literature with general theory on reverse logistics management and performance improvement. To empirically ground the tool, we collect field data by combining quantitative (a multiactor survey) with qualitative (interviews and company visits) methods. We demonstrate how our tool can be used to create awareness at senior management about the reverse logistics maturity state.

In many industries production facilities are used which process products in a batch-wise manner. Guided by research in the aircraft industry, where the process of hardening synthetic aircraft parts was studied, we propose a new control strategy for these types of systems. Given the availability of information on a few near future arrivals the strategy decides on when to schedule a job in order to minimize logistical costs. The fact that different cost structures can be incorporated, makes it a valuable tool for use in practical situations in business. The potential of the new strategy is demonstrated by an extensive series of simulation experiments, in which its response for various system configurations was tested in comparison with existing heuristics. Revision