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International Journal of Machine Learning and Cybernetics
Published in: International Journal of Machine Learning and Cybernetics 4/2018

30-04-2016 | Original Article

Uncertain programming model for multi-item solid transportation problem

Author: Hasan Dalman

Published in: International Journal of Machine Learning and Cybernetics | Issue 4/2018

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Abstract

In this paper, an uncertain Multi-objective Multi-item Solid Transportation Problem (MMSTP) based on uncertainty theory is presented. In the model, transportation costs, supplies, demands and conveyances parameters are taken to be uncertain parameters. There are restrictions on some items and conveyances of the model. Therefore, some particular items cannot be transported by some exceptional conveyances. Using the advantage of uncertainty theory, the MMSTP is first converted into an equivalent deterministic MMSTP. By applying convex combination method and minimizing distance function method, the deterministic MMSTP is reduced into single objective programming problems. Thus, both single objective programming problems are solved using Maple 18.02 optimization toolbox. Finally, a numerical example is given to illustrate the performance of the models.
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Metadata
Title
Uncertain programming model for multi-item solid transportation problem
Author
Hasan Dalman
Publication date
30-04-2016
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Machine Learning and Cybernetics / Issue 4/2018
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-016-0538-7

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