Routing and scheduling in a flexible job shop by tabu search
Annals of Operations Research - Special issue on Tabu search
A Taxonomy of Hybrid Metaheuristics
Journal of Heuristics
Parallel Metaheuristics: A New Class of Algorithms
Parallel Metaheuristics: A New Class of Algorithms
Computers and Operations Research
A genetic algorithm for the Flexible Job-shop Scheduling Problem
Computers and Operations Research
Solving permutational routing problems by population-based metaheuristics
Computers and Industrial Engineering
Flexible job-shop scheduling with parallel variable neighborhood search algorithm
Expert Systems with Applications: An International Journal
A Coarse-Grain Parallel Genetic Algorithm for Flexible Job-Shop Scheduling with Lot Streaming
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 01
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Flexible job shop scheduling using a multiobjective memetic algorithm
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
Flexible job shop scheduling problem by chemical-reaction optimization algorithm
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing
Solving the flexible job shop problem on GPU
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part II
Computers and Industrial Engineering
Flexible job shop scheduling using hybrid differential evolution algorithms
Computers and Industrial Engineering
Path-relinking Tabu search for the multi-objective flexible job shop scheduling problem
Computers and Operations Research
Hi-index | 0.00 |
A parallel approach to flexible job shop scheduling problem is presented in this paper. We propose two double-level parallel metaheuristic algorithms based on the new method of the neighborhood determination. Algorithms proposed here include two major modules: the machine selection module refer to executed sequentially, and the operation scheduling module executed in parallel. On each level a metaheuristic algorithm is used, therefore we call this method meta^2heuristics. We carry out a computational experiment using Graphics Processing Units (GPU). It was possible to obtain the new best known solutions for the benchmark instances from the literature.