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Transport infrastructure investments have been of the highest importance in cities all around the world in order to facilitate people and freight mobility within congested urban areas. This paper studies the problems of freight delivery in congested cities and the location of urban distribution centres. The problem is modelled using the stochastic version of the Location‐Routing Problem in which vehicle...
This paper considers the deterministic vehicle routing problem with service time requirements for delivery. Service requests are also available at different times known at the initial time of route planning. This paper presents an approach based on the generation of service sequences (routes) using randomness. Both the single-vehicle and the multiple-vehicle cases are studied. Our approach is validated...
This paper presents the application Ant Colony Optimization (ACO) to solve multi-criteria combinatorial optimization problems. The proposed decision support technique is validated on the Hybrid Flowshop Scheduling Problem with minimization of both the makespan and the total completion time of jobs. This problem is considered to be strongly NP-hard and has been little studied literature. Our algorithm...
The development of the logistic sector among the last decades has allowed the growth of organizational competitive advantages through the concept of reverse logistics. This concept allows the efficient and effective management of product recycling once they life-cycle is finished. Although the practice of reverse logistics as part of a sustainable strategy for the management of the supply chain, there...
This paper considers the problem of scheduling a set of jobs on both a single machine and identical parallel machines with the objective of minimizing the makespan or maximum completion time of all jobs. Jobs are subject to release dates and there are sequence-dependent setup times. Since this problem is known to be strongly NP-hard even for the single machine case, this paper proposes a heuristic...
The global optimization of complex systems such as industrial systems often necessitates the use of computer simulation. In this paper, we suggest the use of reinforcement learning (RL) algorithms and artificial neural networks for the optimization of simulation models. Several types of variables are taken into account in order to find global optimum values. After a first evaluation through mathematical...
Well-known information is essential for maintaining the market enterprise position and for getting the global performance success in the supply chain. In this paper, we are interested on the analysis, at the operational level, of the production scheduling problem of a manufacturer in a dynamic supply chain context. We consider a simple supply chain, whose members are modeled in an aggregated way and...
This paper addresses the problem of vehicle positioning for automated transport in full-automated manufacturing systems. This study is motivated by the complexity of vehicle control found in semiconductor fabrication where the material handling network path is composed of multiple interconnected loops. We propose an integer linear program that minimizes the maximum time needed to serve a transport...
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