Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5111789 | Omega | 2017 | 24 Pages |
Abstract
In general cases, to find the exact upper bound on the minimal total cost of the transportation problem with varying demands and supplies is an NP-hard problem. In literature, there are only two approaches with several shortcomings to solve the problem. In this paper, the problem is formulated as a bi-level programming model, and proven to be solvable in a polynomial time if the sum of the lower bounds for all the supplies is no less than the sum of the upper bounds for all the demands; and a heuristic algorithm named TPVDS-A based on genetic algorithm is developed as an efficient and robust solution method of the model. Computational experiments on benchmark and new randomly generated instances show that the TPVDS-A algorithm outperforms the two existing approaches.
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Authors
Fanrong Xie, Muhammad Munir Butt, Zuoan Li, Linzhi Zhu,