Learn More
Inspired by nature, genetic algorithms (GA) are among the greatest meta-heuristics optimization methods that have proved their effectiveness to conventional NP-hard problems, especially the traveling salesman problem (TSP) which is one of the most studied supply chain management problems. This paper proposes a new crossover operator called Jump Crossover(More)
  • Salma Mouatassim, Mustapha Ahlaqqach, +4 authors N. Chilov
  • 2016
Several researches have been done to optimize different flows in blood supply chain. However, the use of game theory in this sense is rare. The following work focus on the case of Morocco, consisting of 16 Regional Blood Transfusion Centers (RBTC) centralized around a National Blood Transfusion and Hematology Center (NBTHC). An approach based on hybridized(More)
The aim of this article is to present a collective intelligence approach to help solving optimization problems and apply it in particular to the Travelling Salesman Problem. The approach used is the particle swarm optimization (PSO) whose main idea is to simulate the collective behavior of a cloud. This article also compares the results obtained using PSO(More)
  • Chaouqi M. Benhra, H. Allaoui, +16 authors Jean-Pierre Vernier
  • 2012
Modeling and optimizing joint production-maintenance functions is a part of complex system's representation domain. The exact methods are spread for their simplicity and efficiency. The use of Meta heuristics for optimization problems is the aim of several researches in various domains, enabling us to obtain fast optimal solutions. The focus of this(More)
Hospital mission is to insure patient safety and quality of care associated with any medical processor. Among to provide performance hospitals processors is medicine drugs circuit. Modeling and simulating is an excellent tool that allows understanding this complexity and analyzing performances. In this paper, we propose a simulation models with Colored(More)
  • 1