Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Arnaud Zinflou"'
Publikováno v:
2022 IEEE Electrical Power and Energy Conference (EPEC).
Autor:
François Mirallès, Luc Cauchon, Marc-André Magnan, François Grégoire, Mouhamadou Makhtar Dione, Arnaud Zinflou
Publikováno v:
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.
Publikováno v:
Advances in Evolutionary Algorithms
In many industrial sectors, decision makers are faced with large and complex problems that are often multi-objective. Many of these problems may be expressed as a combinatorial optimization problem in which we define one or more objective functions t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad803ed4ad87ae97f718fad08ad03e27
http://www.intechopen.com/articles/show/title/design_of_an_efficient_genetic_algorithm_to_solve_the_industrial_car_sequencing_problem
http://www.intechopen.com/articles/show/title/design_of_an_efficient_genetic_algorithm_to_solve_the_industrial_car_sequencing_problem
Publikováno v:
Computers & Operations Research. 39:1951-1968
In this paper, we propose a new Pareto generic algorithm, called GISMOO, which hybridizes genetic algorithm and artificial immune systems. GISMOO algorithm is generic in the sense that it can be used to solve both combinatorial and continuous optimiz
Publikováno v:
INFOR: Information Systems and Operational Research. 48:23-37
In this paper, we present three new integrative approaches for solving the classical car-sequencing problem. These hybrid approaches are essentially based on a genetic algorithm which incorporates ...
Publikováno v:
Revue d'intelligence artificielle. 22:209-235
In this paper we propose two forms of hybridization between a metaheuristic (Ant Colony Optimization or Genetic Algorithm) and an exact method (ILP) for the solution of the car sequencing problem. We examine whether such hybridizations can improve so
Publikováno v:
Journal of Heuristics. 14:313-333
Multiple objective combinatorial optimization problems are difficult to solve and often, exact algorithms are unable to produce optimal solutions. The development of multiple objective heuristics was inspired by the need to quickly produce acceptable
Publikováno v:
ECAL
The Genetic Immune Strategy for Multiple Objective Optimization (GISMOO) is a hybrid algorithm for solving multiobjective problems. The performance of this approach has been assessed using a classical combinatorial multiobjective optimization benchma
Autor:
Arnaud Zinflou, Mathieu Viau, Christian Langheit, Luc Vouligny, Mohamed Gaha, Alexandre Bouffard
Publikováno v:
ICSC
The evolution of power distribution systems has considerably increased due to the technologies present in the grid. All these technologies lead to augment the complexity of the information exchanged between heterogeneous applications. One way to addr
Publikováno v:
Metaheuristics for Production Scheduling
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::daf10fd91d111bad7e77de7d044fb019
https://doi.org/10.1002/9781118731598.ch10
https://doi.org/10.1002/9781118731598.ch10