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The Multi -vehicle Traveling Purchaser Problem with Priority in Purchasing and Uncertainty in Demand

Hasanpour Jesri, Zahra Sadat | 2017

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 49979 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Eshghi, Kourosh
  7. Abstract:
  8. Procurement field and supplier’s selection are key decisions in the supply chain in today's business environment.In this problem, both procurement and transportation costs are important. The Traveling Purchasing Problem (TPP) belongs to this field of study. In spite of many researches in the TPP, most of the researches are confined to one single purchaser. In this research, a new variant of Traveling Purchaser Problem is proposed with priority in purchasing. The priority policy is assumed for every single of products and the purchasers’ objective is to meet all of the demands according to their priority and vehicle's capacity in the lowest cost. In this regard, the purchaser has to buy the first priority products in advance and after buying all of the first priority products, should go on purchasing the second priority products. This procedure continues until of buying every product according to its priority. To adjust this model with real problems, it is considered multiple purchasers with predefined capacity. Also the product’s demand is assumed to be uncertain.The goal of this dissertation is to propose a comprehensive integer programming; In this regard, it’s designed a new structure of supplier network in which the suppliers are grouped according to the products’ priority. The Traveling Purchaser Problem with priority in purchasing is NP-hard problem. Therefore, metaheuristic method based genetic algorithm has been developed to obtain acceptable solutions with less computation time. To evaluate its performance, 82 sets of instances have been derived from benchmark
  9. Keywords:
  10. Genetic Algorithm ; Prioritization ; Purchasing System ; Meta Heuristic Algorithm ; Demand Uncertainty ; Traveling Purchaser Problem ; Clustered Supplier's Network ; Multiple Purchaser ; Uncertainty in Demand

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