A PARTICLE SWARM OPTIMIZATION-BASED ALGORITHM FOR JOB-SHOP SCHEDULING PROBLEMS

DOI10.1142/S0219876205000569zbMath1189.90060OpenAlexW2028772506MaRDI QIDQ3573666

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Publication date: 1 July 2010

Published in: International Journal of Computational Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/s0219876205000569

zbMATH Keywords

job-shop schedulingsimilarity measureparticle swarm optimization

Mathematics Subject Classification ID

Deterministic scheduling theory in operations research (90B35)

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Cites Work

• Problem difficulty for tabu search in job-shop scheduling
• A branch-and-bound algorithm for the resource-constrained project scheduling problem
• An efficient genetic algorithm for job shop scheduling with tardiness objectives.
• Some new results on simulated annealing applied to the job shop scheduling problem
• Bidirectional planning: Improving priority rule-based heuristics for scheduling resource-constrained projects
• A branch-and-bound procedure for the multi-mode resource-constrained project scheduling problem with minimum and maximum time lags
• The two-machine flowshop total completion time problem: improved lower bounds and a branch-and-bound algorithm
• A tabu search method guided by shifting bottleneck for the job shop scheduling problem
• A revised simulated annealing algorithm for obtaining the minimum total tardiness in job shop scheduling problems
• A new adaptive neural network and heuristics hybrid approach for job-shop scheduling

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