An efficient heuristic to obtain a better initial feasible solution to the transportation problem

• We develop a better heuristic to obtain a better IFS to the transportation problem.
• We find that 88.9% of the solved problems by JHM led to the optimal solution.
• We demonstrated that the ZSM does not provide the optimal solution all the time.
• The developed JHM is coded using C++ programming language.

Transportation of products from sources to destinations with minimal total cost plays an important role in logistics and supply chain management. All algorithms start with an initial feasible solution in obtaining the minimal total cost solution to this problem. Generally, better is the initial feasible solution lesser is the number of iterations of obtaining the minimal total cost solution. Here, first we demonstrate a deficiency of a recently developed method in obtaining the minimal total cost solution to this problem. Then we develop a better polynomial time (O(N3) (N, higher of the numbers of source and destination nodes)) heuristic solution technique to obtain a better initial feasible solution to the transportation problem. Because of the intractability of carrying out enormous calculations in this heuristic technique without a soft computing program, this technique is coded using C++ programming language. Comparative studies of this heuristic with the best available ones in the literature on results of some numerical problems are carried out to show better performance of the current one. Our heuristic is found to lead to the minimal total cost solution in most cases (88.89%) of the studied numerical problems.

In order to proceed with a minimal total cost solution technique, it is necessary to start with an initial feasible solution (IFS). Thus IFS acts as a foundation to a minimal total cost solution technique to the transportation problem. Generally, better is the initial feasible solution lesser is the number of iterations of obtaining the minimal total cost solution. Here, first we demonstrate a deficiency of a recently developed method in obtaining the minimal total cost solution to this problem. Then we develop a better polynomial time (O(N3) (N, higher of the numbers of source and destination nodes)) heuristic solution technique to obtain a better initial feasible solution to the transportation problem. The developed heuristic is coded using C++ programming language. Comparative studies of this heuristic with the best available ones in the literature on results of some numerical problems are carried out to show better performance of the current one. Our heuristic is found to lead to the minimal total cost solution in most cases (88.89%) of the studied numerical problems.Figure optionsDownload as PowerPoint slide