A genetic algorithm for solving fourth-party logistics routing optimizing problem with fuzzy duration time

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A genetic algorithm for solving fourth-party logistics routing optimizing problem with fuzzy duration time

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ACM/SIGEVO Summit on Genetic and Evolutionary Computation archive
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation table of contents

Shanghai, China

POSTER SESSION: Poster sessions table of contents

Pages 839-842

Year of Publication: 2009

ISBN:978-1-60558-326-6

Authors

Min Huang	Northeastern University, Shenyang, China
Yan Cui	Northeastern University, Shenyang, China
Xingwei Wang	Northeastern University, Shenyang, China
Hongyu Dong	Northeastern University, Shenyang, China

Sponsors

SIGEVO: ACM Special Interest Group on Genetic and Evolutionary Computation
ACM: Association for Computing Machinery

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ACM New York, NY, USA

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ABSTRACT

From the beginning of the 21st century, Fourth Party Logistics (4PL) has been attracting more and more attention in many fields. In this paper, a 4PL routing problem with fuzzy duration time is presented, and the fuzzy numbers is used to denote the uncertainty of the duration time. After a simple description of 4PL, a fuzzy programming for it is built and a crisp equivalent is derived by expected value. Then genetic algorithm is designed to solved the problem. Finally, an extensive computational analysis is presented and the numerical results show that which route should be selected in order to get minimum cost in the due date.

REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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