Procedural Optimization Models for Multiobjective Flexible JSSP

The most challenging issues related to manufacturing efficiency occur if the jobs to be sched-uled are structurally different, if these jobs allow flexible routings on the equipments and mul-tiple objectives are required. This framework, called Multi-objective Flexible Job Shop Scheduling Problems (...

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Bibliographic Details
Published inInformatica Economica Vol. 17; no. 1; pp. 62 - 73
Main Author Nicoara, Elena Simona
Format Journal Article
LanguageEnglish
Published Bucharest INFOREC Association 01.01.2013
Inforec Association
Subjects
Agent-Based Model
Artificial intelligence
Economics
Employment
Equipment costs
Genetic Algorithm
Genetic algorithms
Job shop scheduling
Job shops
JSSP
Linear programming
Manufacturing
Monte Carlo simulation
Multiobjective
Mutation
Optimization
Optimization algorithms
Population
Scheduling
Studies
Workloads
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Summary:The most challenging issues related to manufacturing efficiency occur if the jobs to be sched-uled are structurally different, if these jobs allow flexible routings on the equipments and mul-tiple objectives are required. This framework, called Multi-objective Flexible Job Shop Scheduling Problems (MOFJSSP), applicable to many real processes, has been less reported in the literature than the JSSP framework, which has been extensively formalized, modeled and analyzed from many perspectives. The MOFJSSP lie, as many other NP-hard problems, in a tedious place where the vast optimization theory meets the real world context. The paper brings to discussion the most optimization models suited to MOFJSSP and analyzes in detail the genetic algorithms and agent-based models as the most appropriate procedural models. [PUBLICATION ABSTRACT]
Bibliography:ObjectType-Article-2
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ISSN:1453-1305
1842-8088
DOI:10.12948/issn14531305/17.1.2013.06