A simple algorithm for the multi-objective transportation model

Guo-zhong, Bai; Yao, Lina

doi:10.1109/icbmei.2011.5917951

Cited by 2 publications

(2 citation statements)

References 6 publications

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“…Step 6: Give the equilibrium coefficient 13, and establish the weight of the objectives 12 , ,...., s using equation (3). The weights of the objective are Step 8: Solutions of comprehensive matrix of effect measure using LINGO package.…”

Section: Uumentioning

confidence: 99%

Grey Situation Decision-Making Theory Based New Method for Solving Multi- Objective Transportation

Patel¹,

Dhodiya²

2016

IJMTT

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The transportation problems are framed with multi-goals which are evaluated in various scales and in the meantime in conflict. The many-sided quality of the social and monetary atmosphere require express thought of criteria other than cost around then certifiable issues like delivering an item from a few supply origin to a few interest destination can be formulated as multi-objective transportation models. Grey situation decision making is alluding to the procedure of better choice and shortcoming disposal in which different countermeasure should be preferred according to the different events. This paper applied the grey situation decision making theory for the solution of multi-objective transportation problem.

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Section: Uumentioning

confidence: 99%

Grey Situation Decision-Making Theory Based New Method for Solving Multi- Objective Transportation

Patel¹,

Dhodiya²

2016

IJMTT

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“…Therefore it is necessary to proceed with multi-objectives simultaneously so that firms can get maximum profit. Many researchers have developed efficient techniques for solving two or more objectives simultaneously, which are by Lee et al (1973), , Diaz (1978;, Isermann (1979), Aneja et al (1979), Gupta et al (1983), , , Kasana et al (2000), Chang (2007;2008), Bai et al (2011), Pandian et al (2011), Quddoos et al (2013a and Nomani et al (2017) etc. All techniques developed by these researchers are very difficult to apply and more time consuming.…”

Section: Introductionmentioning

confidence: 99%

An Effective Approach for Solving Multi-objective Transportation Problem

Kaur,

Singh,

Bhandari

et al. 2023

JRSS

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In this present study, a transportation problem is considered such that the total cost and time of transportation are minimized without taking into account their priorities. In literature, there are less techniques available for finding the efficient solutions of multi-objective transportation problem. So, we developed a heuristic algorithm to find most efficient solution of multi-objective transportation problem, which gives efficient solution with minimum difference from ideal solution. Firstly, we aim at formulating a multi-objective transportation problems along with a novel algorithm to find efficient solutions. The proposed algorithm gives optimal solution faster in comparison to other available techniques in literature for the given multi-objective transportation problem. Moreover, it avoids the degeneracy as well as requires low computational effort. Furthermore, an illustrative example is provided to show the feasibility and applicability of the proposed approach and compare the results with the existing approaches to show the effectiveness of it.

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A simple algorithm for the multi-objective transportation model

Cited by 2 publications

References 6 publications

Grey Situation Decision-Making Theory Based New Method for Solving Multi- Objective Transportation

Grey Situation Decision-Making Theory Based New Method for Solving Multi- Objective Transportation

An Effective Approach for Solving Multi-objective Transportation Problem

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