IMPROVING SOLUTION QUALITY IN TRANSPORTATION PROBLEMS: A NOVEL ALGORITHM FOR EFFICIENT RESOURCE ALLOCATION

Abstract

The transportation problem is a critical application in the field of operations research. Finding an optimal solution to transportation problems can be challenging due to the complexity or cost of computer programs involved, as well as the time required for optimization. As a result, obtaining an initial basic feasible solution for the transportation problem has gained significant attention. The objective is to find a systematic approach that produces a solution close to, and at times, even the optimal solution.

In this research paper, we propose the Cost-Quality method (CQM), a novel technique for obtaining an initial basic feasible solution for the transportation problem. CQM aims to maximize the transportation of goods while minimizing the associated costs, incorporating a weighting method-like strategy to achieve the most effective solution. By considering both the quantity of goods transported and the transportation costs, CQM strives to provide an optimal or near-optimal solution to address transportation problems.

Through a comprehensive analysis and experimentation, we evaluate the effectiveness of CQM in comparison to existing methods. We examine its ability to deliver balanced solutions, minimize transportation costs, and achieve computational efficiency. The results demonstrate the advantages and practical implications of CQM, highlighting its potential to improve resource allocation and decision-making processes in transportation planning and logistics.

This research contributes to the advancement of finding initial basic feasible solutions in transportation problems, offering insights into the development of more efficient and effective approaches for solving real-world optimization challenges. With CQM, transportation problem solvers can benefit from enhanced solution quality and computational efficiency, leading to optimized resource utilization and cost reduction.