Genetic learning of dynamic scheduling within a simulation environment

DOI10.1016/0305-0548(94)90020-5zbMath0815.90087OpenAlexW2073458600MaRDI QIDQ1342109

Gary J. Koehler, Jane L. Snowdon, Haldun Aytug

Publication date: 13 February 1995

Published in: Computers \& Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0305-0548(94)90020-5

zbMATH Keywords

simulationgenetic algorithmlearning mode for dynamic scheduling

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Deterministic scheduling theory in operations research (90B35)

Related Items (6)

Executing production schedules in the face of uncertainties: a review and some future directions ⋮ Controlling a re-entrant manufacturing line via the push–pull point ⋮ Genetic clustering algorithms. ⋮ Algorithmical approaches to business process design ⋮ Formulating and solving production planning problems ⋮ Solving large-scale maximum expected covering location problems by genetic algorithms: a comparative study

Cites Work

• Perturbation analysis and optimization of queueing networks
• Perturbation Analysis Gives Strongly Consistent Sensitivity Estimates for the M/G/1 Queue
• A Review of Production Scheduling
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