A novel iterative method to solve a linear fractional transportation problem

IF 1.1 Q3 STATISTICS & PROBABILITY Pakistan Journal of Statistics and Operation Research Pub Date : 2022-03-04 DOI:10.18187/pjsor.v18i1.3889
Sema Akin Bas, Hale Gonce Kocken, Beyza Ahlatcioglu Ozkok
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引用次数: 2

Abstract

The linear fractional transportation problem (LFTP) is widely encountered as a particular type of transportation problem (TP) in real-life. In this paper, a novel algorithm, based on the traditional definition of continuity, is presented to solve the LFTP. An iterative constraint is constructed by combining the objective function of the LFTP and the supply-demand condition since the fractional objective function is continuous at every point of the feasible region. By this constraint obtained, LFTP is converted into an iterative linear programming (LP) problem to reach the optimum solution. In this study, the case of asymptotic solution for LFTP is discussed for the first time in the literature. The numerical examples are performed for the linear and asymptotic cases to illustrate the method, and the approach proposed is compared with the other existing methods to demonstrate the efficiency of the algorithm. Also, an application had environmentalist objective is solved by proposed mathematical method using the software general algebraic modeling system (GAMS) with data set of the real case. Finally, some computational results from tests performed on randomly generated large-scale transportation problems are provided.
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求解线性分式运输问题的一种新的迭代方法
线性分式运输问题(LFTP)作为一种特殊类型的运输问题,在现实生活中广泛存在。本文在传统连续性定义的基础上,提出了一种求解LFTP的新算法。由于分数目标函数在可行区域的每个点都是连续的,因此通过将LFTP的目标函数和供需条件相结合来构造迭代约束。利用该约束条件,将LFTP问题转化为迭代线性规划问题,得到最优解。本文在文献中首次讨论了LFTP渐近解的情形。通过线性和渐近情况下的数值例子来说明该方法,并将所提出的方法与其他现有方法进行比较,以证明该算法的有效性。同时,通过所提出的数学方法,利用具有实际案例数据集的通用代数建模系统(GAMS)软件,解决了一个具有环保目的的应用。最后,给出了对随机产生的大规模运输问题进行测试的一些计算结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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