Fuzzy multi-objective optimization with α-cut analysis for supply chain master planning problem

Abstract

This study considers a supply chain master planning problem in an uncertain environment where operating costs, customer demand, production capacity, manufacturer's acceptable defective rate, and manufacturer's acceptable service level are uncertain. Our supply chain consists of one manufacturer, multiple suppliers, and multiple distribution centers. While one objective is to minimize the total costs of logistics that consists of purchasing cost, production cost, and distribution cost, the other objective is to maximize total value of purchasing. These objectives are in conflict with each other. In this paper, the fuzzy multi-objective linear model is applied with-Cut analysis to achieve the optimal supply chain master planning in an uncertain environment by balancing these two conflicting objectives. The-Cut analysis is introduced to ensure decision-makers that the outcome satisfies their preferences based on a specified minimum allowed satisfaction value ().

A Mathematical Model and Two Fuzzy Approaches Based on Credibility and Expected Interval for Project Cost-Quality-Risk Trade-Off Problem in Time-Constrained Conditions

“…In order to demonstrate the accuracy of the obtained results as well as the advantages of the proposed fuzzy approaches, the introduced project is solved using the fuzzy αcut method [43], which is regarded as another efficient fuzzy solution method, and the presented goal attainment method. The results are presented in Table 5.…”