Transportation problem (TP) is a popular branch of Linear Programming Problem in the field of Transportation engineering. Over the years, attempts have been made in finding improved approaches to solve the TPs. Recently, in Quddoos et al. (Int J Comput Sci Eng (IJCSE) 4(7): 1271–1274, 2012), an efficient approach, namely ASM, is proposed for solving crisp TPs. However, it is found that ASM fails to provide better optimal solution in some cases. Therefore, a new and efficient ASM appoach is proposed in this paper to enhance the inherent mechanism of the existing ASM method to solve both crisp TPs and Triangular Intuitionistic Fuzzy Transportation Problems (TIFTPs). A least-looping stepping-stone method has been employed as one of the key factors to improve the solution quality, which is an improved version of the existing stepping-stone method (Roy and Hossain in, Operation research Titus Publication, 2015). Unlike stepping stone method, least-looping stepping-stone method only deals with few selected non-basic cells under some prescribed conditions and hence minimizes the computational burden. Therefore, the framework of the proposed method (namely LS-ASM) is a combination of ASM (Quddoos et al. 2012) and least-looping stepping-stone approach. To validate the performance of LS-ASM, a set of six case studies and a real-world problem (those include both crisp TPs and TIFTPs) have been solved. The statistical results obtained by LS-ASM have been well compared with the existing popular modified distribution (MODI) method and the original ASM method, as well. The statistical results confirm the superiority of the LS-ASM over other compared algorithms with a less computationl effort.

运输问题（TP）是运输工程领域线性规划问题的一个流行分支。多年来，人们一直在尝试寻找解决 TP 的改进方法。最近，在 Quddoos 等人中。（Int J Comput Sci Eng (IJCSE) 4(7): 1271–1274, 2012）提出了一种有效的方法，即 ASM，用于解决清晰的 TP。然而，发现 ASM 在某些情况下无法提供更好的最优解。因此，本文提出了一种新的高效 ASM 方法，以增强现有 ASM 方法的内在机制，以解决清晰的 TP 和三角直觉模糊运输问题 (TIFTP)。已采用最小循环垫脚石方法作为提高解质量的关键因素之一，这是现有踏脚石方法的改进版本（Roy 和 Hossain in，Operation research Titus Publication，2015 年）。与垫脚石方法不同，最少循环垫脚石方法仅在某些规定条件下处理少数选定的非基本单元格，从而最大限度地减少了计算负担。因此，所提出方法的框架（即 LS-ASM）是 ASM（Quddoos 等人，2012 年）和最少循环踏脚石方法的组合。为了验证 LS-ASM 的性能，已经解决了一组六个案例研究和一个实际问题（包括清晰的 TP 和 TIFTP）。LS-ASM 获得的统计结果也与现有流行的修正分布（MODI）方法和原始 ASM 方法进行了很好的比较。