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Proceedings Paper

Virus evolutionary genetic algorithm for task collaboration of logistics distribution
Author(s): Fanghua Ning; Zichen Chen; Li Xiong
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Paper Abstract

In order to achieve JIT (Just-In-Time) level and clients' maximum satisfaction in logistics collaboration, a Virus Evolutionary Genetic Algorithm (VEGA) was put forward under double constraints of logistics resource and operation sequence. Based on mathematic description of a multiple objective function, the algorithm was designed to schedule logistics tasks with different due dates and allocate them to network members. By introducing a penalty item, make span and customers' satisfaction were expressed in fitness function. And a dynamic adaptive probability of infection was used to improve performance of local search. Compared to standard Genetic Algorithm (GA), experimental result illustrates the performance superiority of VEGA. So the VEGA can provide a powerful decision-making technique for optimizing resource configuration in logistics network.

Paper Details

Date Published: 2 May 2006
PDF: 5 pages
Proc. SPIE 6042, ICMIT 2005: Control Systems and Robotics, 60420N (2 May 2006); doi: 10.1117/12.664555
Show Author Affiliations
Fanghua Ning, Zhejiang Univ. (China)
Zichen Chen, Zhejiang Univ. (China)
Li Xiong, Zhejiang Univ. (China)


Published in SPIE Proceedings Vol. 6042:
ICMIT 2005: Control Systems and Robotics
Yunlong Wei; Kil To Chong; Takayuki Takahashi; Shengping Liu; Zushu Li; Zhongwei Jiang; Jin Young Choi, Editor(s)

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