Supplier evaluation and selection is one of the most important components of supply chain, which influence the long term commitments and performance of the plant. Supplier selection is a complex multi-criteria problem which includes both qualitative and quantitative factors. In order to select the best suppliers it is essential to make a trade off between these tangible and intangible factors some of which may conflict. In this paper, an AHP-based supplier selection model is formulated and then applied to a real case study for a polyamide fiber plant in China. The use of the proposed model indicates that it can be applied to improve and assist decision making to resolve the supplier selection problem in choosing the optimal supplier combination.
Considering the fitness of each individual, a hybrid intelligence algorithm is established, which combine the excellent probing ability of free search algorithm (FS) with exploiting ability of invasive weed optimization algorithm (IWO). The hybrid algorithm can overcome the disadvantage of lower optimization rate in late evolution for FS and taking advantage of powerful exploiting abilities for IWO. Identity between FS and IWO is analyzed and convergence of the two algorithms in solving continuous function optimization is provided. Simulations confirmed the analysis. Multi-model Shubert function is chosen to carry out the simulation. Compared with FS and IWO, the hybrid algorithm is superior in convergence speed and robustness.
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