An interactive possibilistic programming approach for multiple objective supply chain master planning

Providing an efficient production plan that integrates the procurement and distribution plans into a unified framework is critical to achieving competitive advantage. In this paper, we consider a supply chain master planning model consisting of multiple suppliers, one manufacturer and multiple distr...

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Vydáno v:Fuzzy sets and systems Ročník 159; číslo 2; s. 193 - 214
Hlavní autoři: Torabi, S.A., Hassini, E.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Amsterdam Elsevier B.V 16.01.2008
Elsevier
Témata:
Applied sciences
Circuit properties
Compromise solution
Computer science; control theory; systems
Control theory. Systems
Digital circuits
Electric, optical and optoelectronic circuits
Electronic circuits
Electronics
Exact sciences and technology
Information, signal and communications theory
Mathematical methods
Miscellaneous
Mixed-integer linear programs
Possibilistic programming
Supply chain master planning
System theory
Telecommunications and information theory
Theoretical computing
Compromise solution
Mixed-integer linear programs
Supply chain master planning
Possibilistic programming
Fuzzy system
Linear programming
Numerical method
Fuzzy set
Linear model
Integer
Integer programming
Engineering
Numerical solution
Information processing
Distribution function
Problem solving
ISSN:0165-0114, 1872-6801
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Popis
Shrnutí:Providing an efficient production plan that integrates the procurement and distribution plans into a unified framework is critical to achieving competitive advantage. In this paper, we consider a supply chain master planning model consisting of multiple suppliers, one manufacturer and multiple distribution centers. We first propose a new multi-objective possibilistic mixed integer linear programming model (MOPMILP) for integrating procurement, production and distribution planning considering various conflicting objectives simultaneously as well as the imprecise nature of some critical parameters such as market demands, cost/time coefficients and capacity levels. Then, after applying appropriate strategies for converting this possibilistic model into an auxiliary crisp multi-objective linear model (MOLP), we propose a novel interactive fuzzy approach to solve this MOLP and finding a preferred compromise solution. The proposed model and solution method are validated through numerical tests. Computational results indicate that the proposed fuzzy method outperforms other fuzzy approaches and is very promising not only for solving our problem, but also for any MOLP model especially multi-objective mixed integer models.
ISSN:0165-0114
1872-6801
DOI:10.1016/j.fss.2007.08.010