Track: Mathematical Modeling and Heuristics

Abstract

Transportation cost accounts for one to two-thirds of the logistics cost for many organizations. So, minimizing the transportation cost in a Transportation Problem (TP) would help the organization to maximize profit. Though there are various methods, such as linear programming approach, network approach, transportation method, etc., available for addressing TP, the transportation method – particularly any simple and efficient heuristic method (which is expected to give very near optimal solution to TP) – is widely used as this type of method could easily be coupled with any another logistics/supply chain decision-making methods/tools to have an integrated decision-making process. Due to this, many researchers are continuously proposing simple heuristic method(s) for solving TP to get near-optimal solutions. However, from the analysis of the literature, it is observed that there is no good comparative study with good computational experiments considering all heuristic methods, which are (a) claimed as relatively ‘better heuristic method’ and published in reputed journals during the year 2018-2023, (b) evaluated using a large number of tiny test data taken from the literature, and (c) evaluated with large scale test data - generated from popular experimental design available in the literature. To address this research gap, this study considers 7 ‘better heuristic methods’ reported in the literature and proposed 7 heuristic methods. Further, from the detailed performance analyses carried out using (i) large number of tiny test data and (ii) the popular ‘experimental design’ available in the literature, this study identified the ‘best’ heuristic method(s) and the same is reported with insights.