Genetic algorithms and simulated annealing for scheduling in agile manufacturing

DOI10.1080/00207540412331333414zbMath1151.90407OpenAlexW2092632489MaRDI QIDQ5466739

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Publication date: 25 August 2005

Published in: International Journal of Production Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00207540412331333414

zbMATH Keywords

schedulingdigraphsimulated annealinggenetic algorithmsagile manufacturing

Mathematics Subject Classification ID

Deterministic scheduling theory in operations research (90B35) Approximation methods and heuristics in mathematical programming (90C59) Production models (90B30)

Related Items

Deterministic assembly scheduling problems: a review and classification of concurrent-type scheduling models and solution procedures ⋮ An ant colony optimisation algorithm for scheduling in agile manufacturing ⋮ Flow-shop scheduling with setup and assembly operations ⋮ A time-dependent hierarchical Chinese postman problem

Uses Software

• Matlab
• Genocop
• Design-Expert

Cites Work

• Unnamed Item
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• Modified simulated annealing algorithms for the flow shop sequencing problem
• Genetic algorithms for the two-stage bicriteria flowshop problem
• Branch and bound crossed with GA to solve hybrid flowshops
• Application of the simulated annealing algorithm to the combinatorial optimization problem with permutation property: An investigation of generation mechanism
• A genetic algorithm for flowshop sequencing
• Local search algorithms for the multiprocessor flow shop scheduling problem
• Powerful heuristics to minimize makespan in fixed, 3-machine, assembly-type flowshop scheduling
• Simulated annealing and genetic algorithms for scheduling products with multi-level product structure
• A genetic algorithm applied to a classic job-shop scheduling problem
• Scheduling manufacturing systems for delayed product differentiation in agile manufacturing
• An effective hybrid optimization strategy for job-shop scheduling problems