The Solution of Multi-Objective Transportation Problem with Fuzzy Cost and Multi-Choice Demand with Genetic Algorithm Based Approach

Abstract

This paper examines the hybrid approach based on the genetic algorithm (GA) and presents the solution to multi-objective transportation problem (MOTP) with fuzzy cost and multi-choice demand. The exponential membership function with different levels of expectation and shape parameter values is used to give the decision-makers (DM), the greater degree of satisfaction. The proposed work optimizes the multi-objective functions of fuzzy costs by selecting an acceptable demand. This type of situation arises because of the uncertainty in markets requirement. In this problem the cost target functions are not commensurable and conflict with each other. This paper focuses on an approach based on GA in which solution is modified at each step until the condition of termination. To demonstrate the efficacy of the proposed solution, a set of data is given in a numerical example from a practical situation.