Heuristic Approach to Solve Interval Transportation Problem

Abstract

The transportation problem is a special type of linear programming problem in which commodities are transported from a set of sources to a set of destinations subject to the supply and demand quantities of sources and destinations respectively such that the total transportation cost is minimized. This plays an important role in logistics and supply-chain management for improving services, reducing cost, and optimizing the use of resources. Researchers have given considerable attention to the transportation problem with fixed demand and supply. Many algorithms are available to solve transportation problems with the above conditions. However, in realworld applications, demand and supply quantities may vary within a specific interval due to variations in the global economy. Finding an upper minimal total cost of interval transportation problem (ITP) is an NP-hard problem. Thus, less attention has been given to this type of transportation problem. Heuristic approaches are preferred to solve this type of problem. Genetic algorithm is a powerful algorithm to solve NP-hard problems because of its special characteristics. In this paper, a solution procedure based on the concept of a genetic algorithm is proposed to solve ITP.