Abstract:As the most important responsibility of purchasing management, the problem of supplier evaluation and selection has always received a great deal of attention from practitioners and researchers. This management decision is a challenge due to the complexity and various criteria involved. Many methods based on data envelopment analysis(DEA) emerged, especially the cross efficiency. But it exists some limitations, such as the cross efficiency value is often non-unique, average cross efficiency measure is not good because it is not pareto solution. This paper considers the competition between the suppliers and presents game cross efficiency which is based on DEA to assess supplier performance. This method can get a unique efficiency and it is pareto solution. Numerical example is used to illustrate application and feasibility of the proposed methodology.
This paper addressing a study on robust supply chain network design under uncertainty environment. We use decomposition and coordination strategy to decompose the model as two parties: the first part is facility location decision which only concludes 0 − 1 decision variable, tabu search algorithm is used to determine the 0 − 1 decision variables, and then regard the 0 − 1 variables as known input parameters. The second part is flow decision, all-or-nothing method is proposed to design the capacity of the facility. From the numerical example, we can see that, the model and algorithm is valid and effective, the robust optimization model not only reduces the risk of market, but avoids the error from the shortage cost.
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