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1996 | ReviewPaper | Buchkapitel

A comparison of optimization techniques for integrated manufacturing planning and scheduling

verfasst von : M. McIlhagga, P. Husbands, R. Ives

Erschienen in: Parallel Problem Solving from Nature — PPSN IV

Verlag: Springer Berlin Heidelberg

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We describe a comparison between Simulated Annealing (SA), Dispatch Rules (DR), and a Coevolutionary Distributed Genetic Algorithm (DGA) solving a random sample of integrated planning and scheduling (IPS) problems. We found that for a wide range of optimization criteria the DGA consistently outperformed SA and DR. The DGA finds 8–9 unique high quality solutions per run, whereas the other techniques find only one. On average, each DGA solution is 10–15% better than SA solutions and 30–35% better than DR solutions.

Metadaten
Titel
A comparison of optimization techniques for integrated manufacturing planning and scheduling
verfasst von
M. McIlhagga
P. Husbands
R. Ives
Copyright-Jahr
1996
Verlag
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/3-540-61723-X_1024

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