Solving a leader–follower facility problem via parallel evolutionary approaches

A leader–follower facility problem is considered in this paper. The objective is to maximize the profit obtained by a chain (the leader) knowing that a competitor (the follower) will react by locating another single facility after the leader locates its own facility. A subpopulation-based evolutiona...

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Veröffentlicht in:The Journal of supercomputing Jg. 70; H. 2; S. 600 - 611
Hauptverfasser: Arrondo, A. G., Redondo, J. L., Fernández, J., Ortigosa, P. M.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Boston Springer US 01.11.2014
Schlagworte:
Algorithms
Chains
Compilers
Computation
Computer Science
Evolutionary
Interpreters
Mathematical models
Optimization
Parallel processing
Processor Architectures
Programming
Programming Languages
Distributed memory
Nonlinear bi-level programming problem
High performance computing
Shared memory
Evolutionary algorithm
ISSN:0920-8542, 1573-0484
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Zusammenfassung:A leader–follower facility problem is considered in this paper. The objective is to maximize the profit obtained by a chain (the leader) knowing that a competitor (the follower) will react by locating another single facility after the leader locates its own facility. A subpopulation-based evolutionary algorithm called TLUEGO was recently proposed to cope with this hard-to-solve global optimization problem. However, it requires high computational effort, even to manage small-size problems. In this work, three parallelizations of TLUEGO are proposed, a distributed memory programming algorithm, a shared memory programming algorithm, and a hybrid of the two previous algorithms, which not only allow us to obtain the solution faster, but also to solve larger instances.
Bibliographie:ObjectType-Article-1
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ISSN:0920-8542
1573-0484
DOI:10.1007/s11227-014-1106-0