An interior point multiobjective programming approach for production planning with uncertain information

This paper describes a conceptually simple but practical business planning method to cope with uncertain information. The model is constructed by a set of possible scenarios and divided into multiple objective functions. Although the resulting model is more complex than traditional stochastic progra...

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Veröffentlicht in:Computers & industrial engineering Jg. 37; H. 3; S. 631 - 648
Hauptverfasser: Trafalis, Theodore B., Mishina, Tsutomu, Foote, Bobbie L.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York Elsevier Ltd 01.11.1999
Pergamon Press Inc
Schlagworte:
Algorithms
Ellipsoid method
Industrial engineering
Interior point methods
Multiobjective optimization
Production planning
Robust optimization
Stochastic optimization
Studies
Interior point methods
Robust optimization
Stochastic optimization
Production planning
Multiobjective optimization
Ellipsoid method
ISSN:0360-8352, 1879-0550
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Zusammenfassung:This paper describes a conceptually simple but practical business planning method to cope with uncertain information. The model is constructed by a set of possible scenarios and divided into multiple objective functions. Although the resulting model is more complex than traditional stochastic programs, we propose an efficient algorithm in order to offset the difficulties pertaining to the stochastic and multiobjective programming problems. The method provides a wider range of possible solutions. Then the decision maker selects the least conflicting solution among scenarios by incorporating any additional information regarding the problem. An interactive multiobjective programming approach based on a circumscribed ellipsoid interior point algorithm is proposed as an efficient method to solve the problem.
Bibliographie:SourceType-Scholarly Journals-1
ObjectType-Feature-1
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ISSN:0360-8352
1879-0550
DOI:10.1016/S0360-8352(00)00024-3