A genetic algorithm for a bicriteria supplier selection problem |
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Authors: | Chuda Basnet Andres Weintraub |
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Affiliation: | Waikato Management School, The University of Waikato, Hamilton, New Zealand E-mail:; Department of Industrial Engineering, University of Chile, Santiago, Chile E-mail: |
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Abstract: | In this paper, we discuss the problem of selecting suppliers for an organisation, where a number of suppliers have made price offers for supply of items, but have limited capacity. Selecting the cheapest combination of suppliers is a straightforward matter, but purchasers often have a dual goal of lowering the number of suppliers they deal with. This second goal makes this issue a bicriteria problem – minimisation of cost and minimisation of the number of suppliers. We present a mixed integer programming (MIP) model for this scenario. Quality and delivery performance are modelled as constraints. Smaller instances of this model may be solved using an MIP solver, but large instances will require a heuristic. We present a multi-population genetic algorithm for generating Pareto-optimal solutions of the problem. The performance of this algorithm is compared against MIP solutions and Monte Carlo solutions. |
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Keywords: | supplier selection supplier rationalisation bicriteria optimisation genetic algorithm |
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