基于置信度的多目标运输问题

IF 2.2 Q1 MATHEMATICS, APPLIED
Vandana Kakran, J. Dhodiya
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引用次数: 2

摘要

本文主要研究不确定环境下的多选择多目标运输问题。在多选择环境下,将MCMOTP中与目标函数相关的参数视为不确定变量,同时考虑与供给能力和需求需求相关的参数。本文利用两个排序准则将不确定目标转化为清晰的形式。利用这两个排序准则对不确定的MCMOTP模型进行排序,建立了两个确定性模型,即期望值模型(EV模型)和乐观值模型(OV模型)。利用二元变量法将约束条件中的多选择参数转化为单选择参数。利用最小距离法和模糊规划技术,在LINGO 18.0软件中直接求解EV和OV模型。最后,通过数值实例说明了模型的应用和算法。OV模型中目标函数的敏感性也相对于置信水平进行了检验,以研究目标函数的变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A belief-degree based multi-objective transportation problem with multi-choice demand and supply
This paper focusses on the development of a Multi-choice Multi-objective Transportation Problem (MCMOTP) in the uncertain environment. The parameters associated with the objective functions in MCMOTP are regarded as uncertain variables and the other parameters associated with supply capacity and demand requirements are considered under the multi-choice environment. In this paper, two ranking criteria have been utilized to convert the uncertain objectives into their crisp form. Using these two ranking criteria for the uncertain MCMOTP model, two deterministic models have been developed namely, Expected Value Model (EV Model) and Optimistic Value Model (OV Model). The multi-choice parameters in the constraints are converted to a single choice parameters with the help of binary variable approach. The EV and OV models are solved directly in the LINGO 18.0 software using minimizing distance method and fuzzy programming technique. At last, a numerical illustration is provided to demonstrate the application and algorithm of the models. The sensitivity of the objective functions in OV Model is also examined with respect to the confidence levels to investigate variation in the objective functions.
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来源期刊
CiteScore
3.30
自引率
6.20%
发文量
13
审稿时长
16 weeks
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