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A Comparative Study on Heuristic Methods for Transportation Problem.
- Source :
- Proceedings of the International Conference on Industrial Engineering & Operations Management; 2/12/2024, p205-213, 9p
- Publication Year :
- 2024
-
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 2013-2022, (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 10 'better heuristic methods' reported in the literature and proposed 4 heuristic methods. Further, from the detailed performance analyses carried out using 640 randomly generated problem instances, this study identified the 'best' heuristic method(s) and the same is reported with insights. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 21698767
- Database :
- Complementary Index
- Journal :
- Proceedings of the International Conference on Industrial Engineering & Operations Management
- Publication Type :
- Conference
- Accession number :
- 177833203
- Full Text :
- https://doi.org/10.46254/AN14.20240049