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The most frequently studied topic in operational research and computer science is the transportation problem. In general, it is considered here how to reduce the overall cost of transporting goods from each source to another source. But in the case of transportation, transportation costs are only one important factor that is considered. Many other elements must be considered in transportation for real-world applications. The challenge of time-saving transportation provides a powerful foundation for identifying better ways to deliver items to consumers on time. This model was built with the goal of decreasing transportable time. The problems based on transportation time are known as "bottleneck transportation problems (BTP)" or time minimizing transportation problems. The literature attests that various algorithms have been presented to obtain a basic, feasible solution as well as an optimal solution to the BTP. Through this research paper, we hope to introduce a new algorithm to obtain a basic, feasible solution to a bottleneck transportation problem. For that, the new algorithm was built based on the ratio of the unit times in each cell to the total time in the transportation table. By using this method, a basic, feasible solution can be easily obtained for balanced and unbalanced BTPs. The initial solution obtained by using this algorithm is an optimal or near-optimal value. This new algorithm is a relatively effective method that can be easily understood. |