TY - GEN
T1 - Priority-driven Unbalanced Transportation Problem (PUTP) to obtain better Initial Feasible Solution
AU - Arif, Abu Sayeed
AU - Babu, Md Ashraful
AU - Khan, Aminur Rahman
AU - Islam, Mohammad Nazrul
AU - Uddin, Md Sharif
AU - Poonia, Ramesh Chandra
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - In this paper, we tackle the Priority-driven Unbalanced Transportation Problem (PUTP), a scenario where total demand exceeds total supply. An innovative algorithm, the Penalty-driven Priority-driven Unbalanced Transportation Problem (PPUTP) is introduced to solve this challenge. PPUTP allocates supplies to high-priority demands by computing penalties and sequentially addressing the most penalized demands, thereby ensuring priority demands are met efficiently. A comparative analysis with Vogel's Approximation Method (VAM) across various problem sets ranging from 5x5 to 50x50 dimensions demonstrates the efficiency of our algorithms. PPUTP consistently shows lower percentage increments from the optimal solution, indicating its robustness in providing near-optimal solutions. This study highlights the importance of algorithm selection based on problem set dimensions and complexity in Priority-driven Unbalanced Transportation Problem, with PPUTP emerging as a versatile and robust solution across various scenarios.
AB - In this paper, we tackle the Priority-driven Unbalanced Transportation Problem (PUTP), a scenario where total demand exceeds total supply. An innovative algorithm, the Penalty-driven Priority-driven Unbalanced Transportation Problem (PPUTP) is introduced to solve this challenge. PPUTP allocates supplies to high-priority demands by computing penalties and sequentially addressing the most penalized demands, thereby ensuring priority demands are met efficiently. A comparative analysis with Vogel's Approximation Method (VAM) across various problem sets ranging from 5x5 to 50x50 dimensions demonstrates the efficiency of our algorithms. PPUTP consistently shows lower percentage increments from the optimal solution, indicating its robustness in providing near-optimal solutions. This study highlights the importance of algorithm selection based on problem set dimensions and complexity in Priority-driven Unbalanced Transportation Problem, with PPUTP emerging as a versatile and robust solution across various scenarios.
KW - PPUTP
KW - Priority-driven Unbalanced Transportation Problem
KW - VAM
UR - http://www.scopus.com/inward/record.url?scp=85203814159&partnerID=8YFLogxK
U2 - 10.1109/InC460750.2024.10649090
DO - 10.1109/InC460750.2024.10649090
M3 - Conference contribution
AN - SCOPUS:85203814159
T3 - Proceedings of InC4 2024 - 2024 IEEE International Conference on Contemporary Computing and Communications
BT - Proceedings of InC4 2024 - 2024 IEEE International Conference on Contemporary Computing and Communications
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd IEEE International Conference on Contemporary Computing and Communications, InC4 2024
Y2 - 15 March 2024 through 16 March 2024
ER -