TY - JOUR
T1 - A Supply Selection Method for better Feasible Solution of balanced transportation problem
AU - Amaliah, Bilqis
AU - Fatichah, Chastine
AU - Suryani, Erma
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/10/1
Y1 - 2022/10/1
N2 - Transportation Problem (TP) is correlated with product distribution between supply locations and demand locations. TP aims to minimize the total transportation cost, and TP is one of the most important challenges in optimization. To solve the TP, Initial Basic Feasible Solution (IBFS) is a crucial step to determine the Optimal Solution. However, some developed methods of IBFS do not always produce a good initial solution. This study uses a new method called Supply Selection Method (SSM), which is proposed to the get better initial solution for balanced TP. It was compared with other IBFS methods, including Vogel's Approximation Method (VAM), Juman Hoque Method (JHM), Total Opportunity Cost Matrix – Minimal Total (TOCM-MT), and Bilqis Chastine Erma method (BCE) to evaluate the performance. The new method was examined with 45 total cases consisting of 31 cases from some journals, 4 cases generated randomly, and 10 samples of real data from XYZ company. The study results show that SSM provided a better initial basic solution than other methods, with 41 of 45 cases reached the Optimal Solution. The evaluation shows that SSM provided more outcomes with lower total minimal cost than LCM, VAM, JHM, TOCM-MT, and BCE.
AB - Transportation Problem (TP) is correlated with product distribution between supply locations and demand locations. TP aims to minimize the total transportation cost, and TP is one of the most important challenges in optimization. To solve the TP, Initial Basic Feasible Solution (IBFS) is a crucial step to determine the Optimal Solution. However, some developed methods of IBFS do not always produce a good initial solution. This study uses a new method called Supply Selection Method (SSM), which is proposed to the get better initial solution for balanced TP. It was compared with other IBFS methods, including Vogel's Approximation Method (VAM), Juman Hoque Method (JHM), Total Opportunity Cost Matrix – Minimal Total (TOCM-MT), and Bilqis Chastine Erma method (BCE) to evaluate the performance. The new method was examined with 45 total cases consisting of 31 cases from some journals, 4 cases generated randomly, and 10 samples of real data from XYZ company. The study results show that SSM provided a better initial basic solution than other methods, with 41 of 45 cases reached the Optimal Solution. The evaluation shows that SSM provided more outcomes with lower total minimal cost than LCM, VAM, JHM, TOCM-MT, and BCE.
KW - Initial basic feasible solution
KW - Optimal solution
KW - Transportation problem
KW - Vogel's Approximation Method
UR - http://www.scopus.com/inward/record.url?scp=85129893451&partnerID=8YFLogxK
U2 - 10.1016/j.eswa.2022.117399
DO - 10.1016/j.eswa.2022.117399
M3 - Article
AN - SCOPUS:85129893451
SN - 0957-4174
VL - 203
JO - Expert Systems with Applications
JF - Expert Systems with Applications
M1 - 117399
ER -