A learning-based optimization approach to multi-project scheduling

DOI10.1007/s10951-014-0401-1zbMath1310.90058OpenAlexW2053051317MaRDI QIDQ2018943

Katja Verbeeck, Tony Wauters, Patrick de Causmaecker, Greet vanden Berghe

Publication date: 26 March 2015

Published in: Journal of Scheduling (Search for Journal in Brave)

Full work available at URL: https://lirias.kuleuven.be/handle/123456789/466526

zbMATH Keywords

learning automatamulti-project schedulingdispersion games

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Applications of game theory (91A80) Approximation methods and heuristics in mathematical programming (90C59) Queueing theory (aspects of probability theory) (60K25) Stochastic scheduling theory in operations research (90B36) Performance evaluation, queueing, and scheduling in the context of computer systems (68M20) Rationality and learning in game theory (91A26)

Related Items

Multi-project scheduling: a benchmark analysis of metaheuristic algorithms on various optimisation criteria and due dates ⋮ Resource-constrained multi-project scheduling problem: a survey ⋮ A comparison of three heuristics on a practical case of sub-daily staff scheduling ⋮ Negotiation mechanisms for the multi-agent multi-mode resource investment problem ⋮ A learning-based optimization approach to multi-project scheduling ⋮ A modified modeling approach and a heuristic procedure for the multi-mode resource constrained project scheduling problem with activity splitting ⋮ Cellular Automata, Learning Automata, and Cellular Learning Automata for Optimization ⋮ Solving Multi-Mode Resource-Constrained Multi-Project Scheduling Problem with Combinatorial Auction Mechanisms

Uses Software

• MPSPLib

Cites Work

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