TRANSPORTATION PROBLEM, INITIAL BASIC FEASIBLE SOLUTION, IBFS, OPTIMAL SOLUTION, SUPPLY SELECTION METHOD, SSM

• Main Author: Udin, Fadli
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/86649
• Institution: Institut Teknologi Bandung

Research on the transportation problem (TP) plays an important role in the field of logistics and distribution optimization, especially in the era of globalization where supply chains are becoming increasingly complex and have a major impact on the cost efficiency of companies. TP is a type of resource allocation problem that focuses on minimizing the total cost of shipping goods from a number of origin points to several destination points while considering capacity constraints at the origin points and demand at the destination points.There are two stages to obtain the optimal solution of TP, namely using the Initial Basic Feasible Solution (IBFS) method and then the optimization method. The results of IBFS greatly affect the achievement of the optimal solution, and in certain cases, IBFS can directly obtain the optimal solution without having to use the optimization method. One of the IBFS methods that can directly achieve the optimal solution in many cases is the Supply Selection Method (SSM). However, in its application, SSM still cannot solve some TP cases and still contains some ambiguity when satisfying excess rows (ER). This research uses SSM as a basis to build a better IBFS method called the Improved Supply Selection Method (ISSM). ISSM improves the gaps found in SSM and is able to solve TP that cannot be solved by SSM. ISSM is then compared with existing IBFS methods, namely Vogel's approximation method (VAM), SSM, and variants of SSM, namely the Juman Hoque Method (JHM) and the Bilqis Chastine Erma Method (BCE). The test data consists of 45 data, 30 of which come from SSM research (the same data), and the other 15 data come from other studies that discuss TP (new data). The testing process was carried out on a laptop with the following specifications: Processor - 11th Gen Intel Core i5-11400H, 2.70GHz; RAM - 8 GB; Storage - 447GB SSD; and OS - Windows 11 Home Single Language. The research results show that ISSM provides better solutions compared to the other 4 methods, with 39 out of 45 cases reaching optimal solutions. The evaluation shows that ISSM has an accuracy of 100% on "the same data", while SSM only reaches 86.76%. For testing on "new data", ISSM has an accuracy of 60%, better than SSM which only reaches 20%. ISSM improves the performance of the SSM method by 26.7%, with an average execution time difference that is not too far, which is 6.93E-07 seconds.