Papers by Daniel Guimarans
International Journal of Information Systems and Supply Chain Management, 2000
2015 IEEE 34th Symposium on Reliable Distributed Systems (SRDS), 2015
The concept of Smart City is entangled with urban transportation and mobility. Increasing density... more The concept of Smart City is entangled with urban transportation and mobility. Increasing density of urban living, and consequently growing commercial establishments, requires the development of sustainable efficient transportation systems able to deal with the movement of large quantities of goods and services for commercial and domestic use. The role of economic development and structural urban variables, the geographical location, and the density of the population together with the associated congestion problems could have a deep influence in determining the transportation strategy. Therefore, promoting more efficient and intelligent systems, which are applicable in various urban domains with different needs and contextual conditions is a subject of increasing attention.
Lecture Notes in Computer Science, 2000
Routing vehicles to serve customers is a problem that naturally arises in many distribution syste... more Routing vehicles to serve customers is a problem that naturally arises in many distribution systems. Moreover, fleet management requires fast algorithms able to cope with continuously changing needs. Many efforts have been addressed to tackle different vehicle routing problem's variants. Among them, the pick up and delivery problem with time windows (PDTW) has received far less attention despite its relevance from practical and theoretical perspectives. The present paper provides a hybrid approach to the PDTW based on Constraint Programming paradigm and local search. Indeed, the proposed algorithm includes some performance improvements to enhance its efficiency. Thus, this hybrid approach may provide a solution to problems otherwise intractable in a reasonable computational time, as shown in the presented results. Due to these characteristics, the proposed algorithm may be an efficient tool in decision making support, as well as a mechanism able to provide an initial solution for subsequent optimization techniques.
Computers & Operations Research, 2016
In the present paper, we propose a new approach for scheduling ground-handling vehicles, tackling... more In the present paper, we propose a new approach for scheduling ground-handling vehicles, tackling the problem with a global perspective. Preparing an aircraft for its next flight requires a set of interrelated services involving different types of vehicles. Planning decisions concerning each resource affect the scheduling of the other activities and the performance of the other resources. Considering the different operations and vehicles instead of scheduling each resource in isolation allows integrating decisions and contributing to the optimization of the overall ground-handling process. This goal is defined through two objectives: (i) minimizing the waiting time before an operation starts and the total reduction of corresponding time windows and (ii) minimizing the total completion time of the turnarounds. We combine different technologies and techniques to solve the problem efficiently. A new method to address this biobjective optimization problem is also proposed. The approach has been tested using real data from two Spanish airports, thereby obtaining different solutions that represent a trade-off between both objectives. Experimental results permit inferring interesting criteria on how to optimize each resource, considering the effect on other operations. This outcome leads to more robust global solutions and to savings in resources utilization.
This paper presents a metaheuristic methodology based on the Lagrangean Relaxation technique, app... more This paper presents a metaheuristic methodology based on the Lagrangean Relaxation technique, applied to the Travelling Salesman Problem. The presented approach combines the Subgradient Optimization algorithm with a heuristic to obtain a feasible primal solution from a dual solution. Moreover, a parameter has been introduced to improve algorithm convergence. The main advantage is based on the iterative evolution of both upper and lower bounds to the optimal cost, providing a feasible solution in a reasonable number of iterations with a tight gap between the primal and the optimal cost.
Proceedings of the 2010 Summer Computer Simulation Conference, 2010
This paper presents a methodology based on the Variable Neighbourhood Search metaheuristic, appli... more This paper presents a methodology based on the Variable Neighbourhood Search metaheuristic, applied to the Capacitated Vehicle Routing Problem. The presented approach uses Constraint Programming and Lagrangean Relaxation methods in order to improve algorithm's efficiency. The complete problem is decomposed into two separated submodels, to which the mentioned techniques are applied to obtain a complete solution. With this decomposition, the methodology provides a quick initial solution which is rapidly improved by means of metaheuristics' iterative process. Constraint Programming and Lagrangean Relaxation are also embedded within this structure, in order to ensure constraints satisfaction and to reduce the calculation burden. Remarkable results have been obtained using this methodology, including a new best-known solution for a rarely solved 200customers test instance and a better alternative solution for another benchmark problem.
During the last years, the transportation industry has been involved in important new challenges ... more During the last years, the transportation industry has been involved in important new challenges to cope the changes in production and logistical systems. Just-In-Time procurement and quick and efficient consumer response are some of the reasons why the transportation industry has recognized the need to incorporate new information technologies such as Global Positioning System (GPS), Electronic Data Interchange (EDI) and Internet.These technologies can enhance the capabilities to optimize the transport operations since they provide the necessary information required to perform real-time decision making. This paper presents the laboratory environment that is being developed for the design of real-time decision tools for the transportation industry.
This paper presents a metaheuristic methodology based on the Lagrangean Relaxation technique, app... more This paper presents a metaheuristic methodology based on the Lagrangean Relaxation technique, applied to the Travelling Salesman Problem. The presented approach combines the Subgradient Optimization algorithm with a heuristic to obtain a feasible primal solution from a dual solution.
Routing vehicles to serve customers is a problem that naturally arises in many distribution syste... more Routing vehicles to serve customers is a problem that naturally arises in many distribution systems. Moreover, fleet management requires fast algorithms able to cope with continuously changing needs. Many efforts have been addressed to tackle different vehicle routing problem's variants. Among them, the pick up and delivery problem with time windows (PDTW) has received far less attention despite its relevance from practical and theoretical perspectives. The present paper provides a hybrid approach to the PDTW based on Constraint Programming paradigm and local search. Indeed, the proposed algorithm includes some performance improvements to enhance its efficiency. Thus, this hybrid approach may provide a solution to problems otherwise intractable in a reasonable computational time, as shown in the presented results. Due to these characteristics, the proposed algorithm may be an efficient tool in decision making support, as well as a mechanism able to provide an initial solution for subsequent optimization techniques.
In a recent study we showed that there exists significant unrealised rail capacity at Sydney'... more In a recent study we showed that there exists significant unrealised rail capacity at Sydney's Port Botany. Unlocking this capacity depends on better management of rail resources, including improved staging and scheduling practices. We study the impact of several such changes: (i) we replace fixed servicing windows with anytime servicing; (ii) we apply constraints to train length and rake utilisation; (iii) we schedule and stage trains holistically, between the port and intermodal terminals in the Sydney area. We aim to consolidate trains and move the same container volumes with fewer trips.
We employ a simulation approach to analyse the operations of container-freight trains in and arou... more We employ a simulation approach to analyse the operations of container-freight trains in and around Sydney's Port Botany. Our objective is to evaluate the current performance of rail, as well as investigating the peak rail capacity of both current and proposed infrastructure. Contrary to popular perceptions, we found that there exists significant unrealised capacity at the port and achieving it depends only on operational changes. Moreover, proposed infrastructural upgrades, including a centralised terminal and duplication of some track, appear to yield little benefit over the medium term.
Preparing an aircraft for its next flight requires a set of interrelated services involving diffe... more Preparing an aircraft for its next flight requires a set of interrelated services involving different types of vehicles. Planning decisions concerning each resource affect the scheduling of the other activities and the performance of the other resources. Considering the different operations and vehicles instead of scheduling each resource in isolation allows integrating decisions and contributing to the optimisation of the overall ground-handling process. This goal is defined through two objectives: (i) minimising the waiting time before an operation starts and the total reduction of corresponding time windows, and (ii) minimising the total completion time of turnarounds. We combine different technologies and techniques to solve the problem efficiently. A new method to address this bi-objective optimisation problem is also proposed. The approach has been tested using real data from a major Spanish airport, obtaining different solutions that represent a trade-off between both objecti...
It is said that there is more than one way to skin a cat. The same is true of solving long-haul t... more It is said that there is more than one way to skin a cat. The same is true of solving long-haul transportation problems. We explore seven different approaches for solving a real-world multi-commodity long-haul transportation problem. The problem features a heterogeneous fleet with capacity constraints, compatibility constraints between commodities and trucks (e.g., refrigerated goods can only travel on refrigerated trucks), and demands which require split deliveries. The problem has been studied at the request of a Queensland-based transportation company, which provided historical data concerning orders, and fleet data. Among the explored approaches are: an educated random sampling coupled with a nearest-neighbour heuristic, a step-based constraint programming approach, a route selection approach which relies on a custom pre-processing phase, an answer set programming formulation, a large neighbourhood search approach based on the classic vehicle routing formulation, an integer line...
We propose a methodology combining simulation and optimisation to tackle operational disruptions ... more We propose a methodology combining simulation and optimisation to tackle operational disruptions in the airline industry and increase solutions resilience. Operational disruptions are defined as a deviation from originally planned operations and cause significant overheads to airlines. By introducing Monte-Carlo simulation methods within the solution acceptance mechanism in a Large Neighbourhood Search process, we can guide search towards more robust solutions. Advantages of our proposed methodology will be assessed by different case studies based on real data. Reference: Daniel Guimarans, Pol Arias, Miguel A. Mújica Mota. A large neighbourhood search combined with Monte Carlo simulation to cope with airlines operational disruptions.
This paper presents a hybrid approach that aims at solving the Capacitated Vehicle Routing Proble... more This paper presents a hybrid approach that aims at solving the Capacitated Vehicle Routing Problem (CVRP) by means of combining Constraint Programming (CP) with Lagrangian Relaxation (LR) and Probabilistic Algorithms. After introducing the CVRP and reviewing the main literature on this area, the paper proposes the use of a multistart hybrid Variable Neighbourhood Search (VNS) algorithm. This algorithm uses a randomised version of the classical Clarke and Wright savings heuristic to generate a starting solution to a given CVRP. This starting solution is then improved through a local search process which combines: (a) LR to optimise each individual route, and (b) CP to quickly verify the feasibility of new proposed solutions. Some results on well-known CVRP benchmarks are analysed and discussed.
Applied Simulation and Optimization, 2015
ABSTRACT The airline industry is one of the most affected by operational disruptions, defined as ... more ABSTRACT The airline industry is one of the most affected by operational disruptions, defined as deviations from originally planned operations. Due to airlines network configuration, delays are rapidly propagated to connecting flights, substantially in- creasing unexpected costs for the airlines. The goal in these situations is therefore to minimise the impact of the disruption, reducing delays and the number of affected flights, crews and passengers. In this chapter, we describe a methodology that tackles the Stochastic Aircraft Recovery Problem, which considers the stochastic nature of air transportation systems. We define an optimisation approach based on the Large Neighbourhood Search metaheuristic, combined with simulation at different stages in order to ensure solutions’ robustness. We test our approach on a set of instances with different characteristics, including some instances originating from real data provided by a Spanish airline. In all cases, our approach performs better than a deterministic approach when system’s variability is considered.
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Papers by Daniel Guimarans