Transportation problem is dealing with the problems of optimal transportation of available allocation of resources. Solving a transportation problem involves decision parameters like availability, requirements, and unit transportation cost in a crisp environment. But in real life situations precise values of the parameters may not be easily available. This uncertainty leads way for including the fuzziness in the decision parameters at different levels. Further obtaining an initial basic feasible solution is the prime requirement to find an optimal solution for the crisp transportation problems and fuzzy transportation problems. In the present study, a new approach, Reduced Row-Column Matrix (RRCM) method, is proposed to find an initial basic feasible solution to crisp as well as fuzzy transportation problem. The method is tested with numerical examples. From the analysis of the results, it is evident that the solution of the proposed method gives better results for both types of transportation problems rather than the existing algorithms.

crisp transportation problem, fuzzy transportation problem, initial basic feasible solution, reduced row-column matrix.