Parallel meta2heuristics for the flexible job shop problem

Authors:
Wojciech Bożejko;Mariusz Uchroński;Mieczysław Wodecki
Affiliations:
Institute of Computer Engineering, Control and Robotics, Wrocław University of Technology, Wrocław, Poland;Institute of Computer Engineering, Control and Robotics, Wrocław University of Technology, Wrocław, Poland;Institute of Computer Science, University of Wrocław, Wrocław, Poland
Venue:
ICAISC'10 Proceedings of the 10th international conference on Artifical intelligence and soft computing: Part II
Year:
2010

Citing 4
Cited 2

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A hybrid genetic and variable neighborhood descent algorithm for flexible job shop scheduling problems

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A genetic algorithm for the Flexible Job-shop Scheduling Problem

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Scheduling: Theory, Algorithms, and Systems

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Iterative flattening search for the flexible job shop scheduling problem

IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
An integrated search heuristic for large-scale flexible job shop scheduling problems

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Abstract

In this paper we consider a double-level metaheuristic optimization algorithm. The algorithm proposed here includes two major modules: the machine selection module which is executed sequentially, and the operation scheduling module executed in parallel. On each level a metaheuristic algorithm is used, so we call this method meta2heuristics. We carry out computational experiment using Graphics Processing Units (GPU). It was possible to obtain new the best known solutions for the benchmark instances from the literature.