An Integrated Supplier Selection and Order Allocation with Quantity Discounts under Uncertainty

Document Type : Article


Department of Industrial Engineering, Imam Hossein University (IHU), Tehran, Iran


Supplier selection and order allocation decisions are the main parties of a supply chain network which has a high impact on the economic performance of this network. This study using an Economic Order Quantity (EOQ) concept proposes an optimization model for the integrated supplier selection and order allocation problem where lot sizing, discounts, and disruptions are contributed among the first studies in this research area. To address the uncertainty, scenario-based stochastic programming is employed to consider both operational and disruption uncertainties. For solving the proposed model, not only the exact solver is employed but also an innovative algorithm based on a hybrid algorithm using Particle Swarm Optimization (PSO) and the Imperialist Competitive Algorithm (ICA) is utilized. To enhance the performance of our metaheuristic algorithm, the Taguchi experimental design method is employed. Some sensitivity analyses on the key parameters of our optimization model are done accordingly. The main findings are the performance of the proposed algorithm for solving large-scale tests and the practicality of the proposed model to address lot sizing, discounts, and disruptions.


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