Abstract
In this paper, we extend the classical assignment problem to the multicriteria assignment problem by considering three criteria: cost, time and quality subject to many realistic constraints including multi-job assignment and a knapsack-type resource constraint. The paper addresses the uncertainty of the real-life assignment problem by formulating a fuzzy cost–time–quality assignment problem using exponential membership functions. We define fuzzy goal for each criterion as per the preferences of the decision-maker and aggregate the fuzzy goals using product operator. In order to obtain optimal assignment plans, the resultant nonlinear 0-1 optimization problem is solved using genetic algorithm for different choices of the shape parameters in the exponential membership functions. As an illustrative example, we consider a fuzzy manpower planning problem.
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We are thankful to the Editor-in-Chief Professor Xi-Zhao Wang and the anonymous referees for their valuable comments and suggestions to improve presentation of the paper.
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Gupta, P., Mehlawat, M.K. & Mittal, G. A fuzzy approach to multicriteria assignment problem using exponential membership functions. Int. J. Mach. Learn. & Cyber. 4, 647–657 (2013). https://doi.org/10.1007/s13042-012-0122-8
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DOI: https://doi.org/10.1007/s13042-012-0122-8