The maximum range method for finding initial basic feasible solution for transportation problems

The transportation problem is an essential branch of mathematics that industries use to minimize costs. The transportation problem is an optimization technique suitably modeled using linear programming. To obtain an optimal solution to the transportation problem, first compute the initial basic feasible solution, which is then subsequently optimized. Several algorithms, like Vogel’s approximation method, maximum difference extreme difference method, demand-based allocation method, and others, are used in literature to determine the initial basic feasible solution to these transportation problems. This paper proposes a robust algorithm that can produce an initial basic feasible solution asymptotic to the optimal solution. The study further carried out a performance analysis by comparing the proposed algorithm’s results with those of some existing algorithms. The observation was that the proposed algorithm in many cases produced an optimal initial basic feasible solution (IBFS) for both balanced and unbalanced transportation problems and also tend to have a very high average of correctness percentage compared to some existing algorithms.

Authors

Publication Details

Journal
Results in Control and Optimization
Published
2025-04-08
DOI
https://doi.org/10.1016/j.rico.2025.100551
Citations
2
Primary Topic
Optimization and Mathematical Programming
Type
article
Field-Weighted Citation Impact
2.43
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article

The maximum range method for finding initial basic feasible solution for transportation problems

Joseph Ackora-Prah, Charles Sebil, Fredrick Asenso Wireko, Ignatius Dennis Kwesi Mensah et al.
2 citations
Results in Control and Optimization
Optimization and Mathematical Programming
2.43
article

The maximum range method for finding initial basic feasible solution for transportation problems

Joseph Ackora-Prah, Charles Sebil, Fredrick Asenso Wireko, Ignatius Dennis Kwesi Mensah, Emmanuel Nii Apai Aborhey, Samuel Adu Appiah
article en
2 citations

Abstract

The transportation problem is an essential branch of mathematics that industries use to minimize costs. The transportation problem is an optimization technique suitably modeled using linear programming. To obtain an optimal solution to the transportation problem, first compute the initial basic feasible solution, which is then subsequently optimized. Several algorithms, like Vogel’s approximation method, maximum difference extreme difference method, demand-based allocation method, and others, are used in literature to determine the initial basic feasible solution to these transportation problems. This paper proposes a robust algorithm that can produce an initial basic feasible solution asymptotic to the optimal solution. The study further carried out a performance analysis by comparing the proposed algorithm’s results with those of some existing algorithms. The observation was that the proposed algorithm in many cases produced an optimal initial basic feasible solution (IBFS) for both balanced and unbalanced transportation problems and also tend to have a very high average of correctness percentage compared to some existing algorithms.

Results in Control and OptimizationVol. 19
Openalex Percentile: Top 12%
Optimization and Mathematical Programming
2.43
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