A novel fuzzy stochastic multi-objective linear programming for multi-level capacitated lot-sizing problem: a real case study of a furniture company

This paper develops a fuzzy stochastic multi-objective linear programming model for a multi-level, capacitated lot-sizing problem (ML-CLSP) in a mixed assembly shop. The proposed model aims to minimize the total cost consisting of total variable production cost, inventory cost, backorder cost, and s...

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Vydáno v:International journal of advanced manufacturing technology Ročník 84; číslo 1-4; s. 749 - 767
Hlavní autoři: Sahebjamnia, Navid, Jolai, F., Torabi, S. A., Aghabeiglo, Mohsen
Médium: Journal Article
Jazyk:angličtina
Vydáno: London Springer London 01.04.2016
Springer Nature B.V
Témata:
CAE) and Design
Computer-Aided Engineering (CAD
Engineering
Furniture
Industrial and Production Engineering
Linear programming
Lot sizing
Mathematical models
Mechanical Engineering
Media Management
Multiple objective analysis
Original Article
Process parameters
Production costs
Mixed assembly shop
Production planning
Fuzzy stochastic multi-objective programming
Multi-level capacitated lot-sizing problem
ISSN:0268-3768, 1433-3015
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Shrnutí:This paper develops a fuzzy stochastic multi-objective linear programming model for a multi-level, capacitated lot-sizing problem (ML-CLSP) in a mixed assembly shop. The proposed model aims to minimize the total cost consisting of total variable production cost, inventory cost, backorder cost, and setup cost while maximizing the resource utilization rate simultaneously. To cope with inherent mixed fuzzy stochastic uncertainty associated with input data, e.g., the demand and process-related parameters, they are treated as fuzzy stochastic parameters. We conducted a numerical example from literature to illustrate the efficiency of the proposed method against other ones. To validate the expediency of the proposed ML-CLSP and solution method, a real case study was executed in a furniture company. The results demonstrate the usefulness of the proposed model and its solution approach.
Bibliografie:ObjectType-Case Study-2
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ISSN:0268-3768
1433-3015
DOI:10.1007/s00170-015-7735-5