The increasing customer expectations for customized products of high quality in short delays and the worldwide competition in terms of quality and costs have pushed industries to implement new strategies to manage their supply chain decisions. In this context, the integrated planning is becoming the most dominant over the operational research field because of its efficiency and its ability to cover the different aspects of the problem. Production routing problem is one of the problems of the integrated planning that is of interest in optimizing simultaneously production, inventory, and distribution planning. This paper has the purpose of developing two mono-objective models for the production-routing problem; one of them minimizes the total costs, while the other one minimizes the energy consumed by the production system. Finally, a bi-objective model is proposed to combine the two objectives mentioned previously using the LP-metric method in the context of a sustainable supply chain. Experimental results are also presented and discussed through the different scenarios.
In this paper, the authors' interest is focused on the scheduling problem on identical parallel machines with consumable resources in order to minimize the makespan criterion. Each job consumes several components which arrive at different times. The arrival of each component is represented by a curve-shaped staircase. This problem is NP-hard, further, there are not universal methods making it possible to solve all the cases effectively, especially for medium or large instances. A genetic algorithm is proposed to solve this problem due to proven great performance in solving combinatorial optimization problems. To check its effectiveness this algorithm is compared with an exact resolution method which enumerates all possible solutions for small instances and with a heuristic for large instances. Various randomly generated instances, which can represent realistic situations, are tested. The computation results show that this algorithm outperforms heuristic procedure and is tailored for larger scale problems.
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