A 2-Phase Method for Solving Transportation Problems with Prohibited Routes

IF 1.1 Q3 STATISTICS & PROBABILITY Pakistan Journal of Statistics and Operation Research Pub Date : 2022-09-10 DOI:10.18187/pjsor.v18i3.3911
Joseph Ackora Prah, Valentine Acheson, B. Barnes, I. Takyi, E. Owusu-Ansah
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引用次数: 1

Abstract

The Transportation Problem (TP) is a mathematical optimization technique which regulates the flow of items along routes by adopting an optimum guiding principle to the total shipping cost. However, instances including road hazards, traffic regulations, road construction and unexpected floods sometimes arise in transportation to ban shipments via certain routes. In formulating the TPs, potential prohibited routes are assigned a large penalty cost, M, to prevent their presence in the model solution. The arbitrary usage of the big M as a remedy for this interdiction does not go well with a good solution. In this paper, a two-phase method is proposed to solve a TP with prohibited routes. The first phase is formulated as an All-Pairs Least Cost Problem (APLCP) which assigns respectively a non-discretionary penalty cost M*ij <= M to each of n prohibited routes present using the Floyd¢s method. At phase two, the new penalty values are substituted into the original problem respectively and the resulting model is solved using the transportation algorithm. The results show that, setting this modified penalty cost ( M*) logically presents a good solution. Therefore, the discretionary usage of the M <= ∞ is not a guarantee for good model solutions. The modified cost M*<= M so attained in the sample model, is relatively less than the Big M ( <= ∞) and gives a good solution which makes the method reliable.
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带禁行路线的交通问题的两阶段解法
运输问题(TP)是一种数学优化技术,通过对总运输成本采用最优指导原则来调节货物沿路线的流动。然而,在运输中有时会出现道路危险、交通法规、道路建设和意外洪水等情况,以禁止通过某些路线运输。在制定TPs时,潜在的禁止路径被分配了一个大的惩罚成本M,以防止它们出现在模型解中。任意使用大M作为这种封锁的补救措施并不适合一个好的解决方案。本文提出了一种两阶段法来解决带有禁止路由的TP问题。第一阶段是一个全对最小代价问题(APLCP),该问题使用Floydⅱ方法对n条存在的禁止路线分别分配一个非任意处罚代价M*ij <= M。在第二阶段,将新的惩罚值分别代入原问题,并使用运输算法求解得到的模型。结果表明,在逻辑上设置修正后的惩罚成本(M*)是一个较好的解决方案。因此,任意使用M <=∞并不能保证得到好的模型解。在样本模型中得到的修正代价M*<= M,相对小于大M(<=∞),并给出了很好的解,使方法可靠。
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来源期刊
CiteScore
3.30
自引率
26.70%
发文量
53
期刊介绍: Pakistan Journal of Statistics and Operation Research. PJSOR is a peer-reviewed journal, published four times a year. PJSOR publishes refereed research articles and studies that describe the latest research and developments in the area of statistics, operation research and actuarial statistics.
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