Modeling the bidding approach and its application for the procurement of relief items

Document Type : Research Paper

Authors

1 School of Industrial Engineering, Urmia University of Technology, Urmia, Iran.

2 Ass. of Faculty of Industrial Engineering, Uremia University of technology faculty member- Uremia- IRAN

3 3- Assistant prof., School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran.

Abstract

Supplier selection and order allocation in the process of purchasing relief items during critical conditions are important issues. In this paper, the mixed approach of Multi-criteria decision making and mathematical programming model have been represented in order to select suppliers and allocate orders in the framework of Multi-attribute reverse auction. The suggested approach has been modeled focusing on bid evaluation phase in
 Two stage. In the first stage, each participator in the bid is ranked using the Fuzzy-PROMETHEE method as the supplier of assistance items regarding effective quantitative and qualitative criteria. In the second stage, suitable suppliers are selected based on priorities of the first stage, in the frame of a multi-objective fuzzy mathematical model in order to determine the optimal size of ordering. Disruption risk in both distribution centers and suppliers, as well as the uncertainty including major features of the mathematical model have been represented. In this paper, multi-objective robust possibility programming (MORPP) approach has been used in order to eliminate the uncertainty of parameters related to purchasing assistance items within the humanitarian relief supply chains. To solve the multi-objective model the augmented e-constraint method has been considered. Finally, calculation results are indicative of better performance and efficiency of the MORPP approach to solve purchasing assistance items problem.

Keywords

Main Subjects


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Volume 22, Issue 87 - Serial Number 87
November 2018
Pages 67-100
  • Receive Date: 26 February 2018
  • Revise Date: 13 June 2018
  • Accept Date: 17 June 2018
  • First Publish Date: 23 August 2018