Robust Optimization of Inventory in Supply Chain Management

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AminGhafouri, Reza | 2014

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Type of Document: M.Sc. Thesis
Language: Farsi
Document No: 46306 (01)
University: Sharif University of Technology
Department: Industrial Engineering
Advisor(s): Modarres Yazdi, Mohammad
Abstract:
In this research, the determination of inventory management policy is investigated in two-level supply chains. Two scenarios are considered to analyze this problem. In the first one, all parameters are assumed to be deterministic while in the other one, the retailer’s demand is assumed to be uncertain. We extend the previous studies by considering the real world conditions; and introduce a model in which the costs of lost-sale and backorder are considered simultaneously. A genetic algorithm is developed to solve the proposed model. To evaluate the efficiency of the model, the results are compared over five different examples when only complete backorder is considered. In case of uncertain scenario, we apply the Bertsimas and Sim method, because of its better efficiency in modelling integer problems as well as its adjustability of rate of uncertainty. To evaluate this method, a numerical example is solved by using a new Genetic Algorithm considering different levels of protection. The obtained results show the capability of robust optimization in solving problems in uncertainty conditions with acceptable accuracies
Keywords:
Inventory Control ; Genetic Algorithm ; Supply Chain ; Robust Optimization

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