An improved constraint satisfaction adaptive neural network for job-shop scheduling

DOI10.1007/S10951-009-0106-ZzbMath1185.90103OpenAlexW2111143264WikidataQ59569463 ScholiaQ59569463MaRDI QIDQ969749

Graham Kendall, Shengxiang Yang, Dingwei Wang, Tian-You Chai

Publication date: 7 May 2010

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

Full work available at URL: http://bura.brunel.ac.uk/handle/2438/5984

zbMATH Keywords

computational complexityheuristicsjob-shop schedulingpriority ruleactive scheduleconstraint satisfaction adaptive neural networknon-delay schedule

Mathematics Subject Classification ID

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

Uses Software

• OR-Library

Cites Work

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• A survey of priority rule-based scheduling
• A Review of Production Scheduling
• Technical Note—Finding Some Essential Characteristics of the Feasible Solutions for a Scheduling Problem
• The Complexity of Flowshop and Jobshop Scheduling
• Optimization and Approximation in Deterministic Sequencing and Scheduling: a Survey
• Algorithms for Solving Production-Scheduling Problems
• A new adaptive neural network and heuristics hybrid approach for job-shop scheduling

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