Title: A robust possibilistic programming model for simultaneous decision of inventory lot-size, supplier selection and transportation mode selection
Authors: Atousa Zarindast; Seyed Mohamad Seyed Hosseini; Mir Saman Pishvaee
Addresses: School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran ' School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran ' School of Industrial Engineering, Iran University of Science and Technology, Tehran, Iran
Abstract: As a result of the uncertain changes in global currencies, exchange rates have become a critical part of suppliers' selection problem. In the present paper the problem of supplier, transportation mode selection and inventory replenishment decision (STSI) in the presence of uncertain changes of currency exchange rates and price discounts have been studied. The present article addresses the STSI problem for a buyer sourcing a product from heterogeneous suppliers. Global suppliers' selection procedure is based on the prices that suppliers offer in their local currencies. Late deliveries and rejections also exert influence on sourcing and inventory replenishment decisions. The proposed model is a bi-objective mathematical programming, objective functions of which are minimising the total cost and the late delivery of items. In order to cope with uncertain parameters effectively, a robust possibilistic programming approach is utilised. Finally, to assess the robustness of the solutions obtained by the novel robust optimisation model, our model's results are compared to those generated by the chance-constrained programming model under the data of STAM SANAT Company. Further, the advantages of using this integrated approach versus a sequential approach under currency fluctuations are shown.
Keywords: supplier selection; lot-size; transportation mode selection; robust programming; RP; discount; currency exchange rate uncertainty.
International Journal of Industrial and Systems Engineering, 2018 Vol.30 No.3, pp.346 - 364
Received: 16 Aug 2016
Accepted: 12 Nov 2016
Published online: 09 Oct 2018 *