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Management Science Letters

ISSN 1923-9343 (Online) - ISSN 1923-9335 (Print)
Quarterly Publication
Volume 4 Issue 9 pp. 2155-2160 , 2014

An approach for solving multi-objective assignment problem with interval parameters Pages 2155-2160 Right click to download the paper Download PDF

Authors: Kayvan Salehi

Keywords: Assignment problem, Integer programming, Interval number, Weighted min-max method

Abstract: This paper presents a multi-objective assignment problem (MAP) with interval parameters. Here, the model concentrates on three criteria: total cost, total profit and total operation time of assignment. The proposed model is classified as a nonlinear programming, in which it is difficult to solve. Hence, the model is converted into crisp linear programming problem by applying a substitution variables approach. In addition, a weighted min-max method is applied to transform the multi-objective problem into a single objective optimization problem. Finally, several numerical examples are provided to illustrate the implementation of the proposed approach. The results clearly provide some evidences that the proposed approach was easier to contrast compared with other approaches. The results also indicate that decision makers’ preferences over various objectives could influence on solutions.

How to cite this paper
Salehi, K. (2014). An approach for solving multi-objective assignment problem with interval parameters.Management Science Letters , 4(9), 2155-2160.

Refrences
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Bogomolnaia, A. (2001). A new solution to the random assignment problem. Journal of Economic Theory, 100, 295–328.

Bogomolnaia, A., & Moulin, H. (2002). A simple random assignment problem with a unique solution. Economic Theory, 19(3), 623-636.

Coppersmith, D., & Sorkin, G.B. (1999). Constructive bounds and exact expectation for the random assignment problem. Random Structure Algorithm, 15(2), 113–144.

Feng, Y., & Yang, L. (2006). A two-objective fuzzy k-cardinality assignment problem. Journal of Computational Applied Mathematics, 197, 233–244.

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Liu, L., & Gao, X. (2009). Fuzzy weighted equilibrium multi-job assignment problem and genetic algorithm. Applied Mathematical Modeling, 33, 3926–3935.

Liu, L., & Li, Y. (2006). The fuzzy quadratic assignment problem with penalty: new models and genetic algorithm. Applied Mathematical Computation, 174, 1229–1244.

Marler, R. T., & Arora, J. S. (2004). Survey of multi-objective optimization methods for engineering. Structural and multidisciplinary optimization, 26(6), 369-395.

Mukherjee, S., & Basu, K. (2010). Application of fuzzy ranking method for solving assignment problems with fuzzy costs. International Journal of Computational and Applied Mathematics, 5, 359-368.

Mukherjee, S., & Basu, K. (2011). Solving intuitionistic fuzzy assignment problem by using similarity measures and score functions. International Journal of Pure and Applied Sciences and Technology, 2(1), 1-18.

Ridwan, M. (2004). Fuzzy preference based traffic assignment problem. Transportation Research Part C, 12, 209–233.

Saati, S., Memariani, A., & Jahanshahloo, G.R. (2002). Efficiency analysis and ranking of decision making units with fuzzy data. Fuzzy Optimization and Decision Making, 1(3), 255-267.

Zhou, F., Huang, G.H., Chen, G.X., & Guo, H.C. (2009). Enhanced-interval linear programming. European Journal of Operational Research, 199, 323–333
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Journal: Management Science Letters | Year: 2014 | Volume: 4 | Issue: 9 | Views: 3178 | Reviews: 0

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