Job Shop Scheduling by Simulated Annealing

We describe an approximation algorithm for the problem of finding the minimum makespan in a job shop. The algorithm is based on simulated annealing, a generalization of the well known iterative improvement approach to combinatorial optimization problems. The generalization involves the acceptance of...

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Veröffentlicht in:	Operations research Jg. 40; H. 1; S. 113 - 125
Hauptverfasser:	van Laarhoven, Peter J. M, Aarts, Emile H. L, Lenstra, Jan Karel
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Linthicum, MD INFORMS 01.01.1992 Operations Research Society of America Institute for Operations Research and the Management Sciences
Schlagworte:	Algorithms analysis of algorithms Applied sciences Approximation Combinatorial optimization Cooling Cost efficiency deterministic Ergodic theory Exact sciences and technology Experiments Heuristics job shop scheduling Job shops Markov chains multiple machine Operational research and scientific management Operational research. Management science Operations research Optimization Production scheduling production/scheduling, sequencing Scheduling Scheduling, sequencing Simulated annealing Simulation suboptimal algorithms Markov chain Experimental result Approximation Simulated annealing Job shop Scheduling Asymptotic convergence Algorithm analysis
ISSN:	0030-364X, 1526-5463
Online-Zugang:	Volltext
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