[1] Xu Hang, Xu Rong, Ye Qingtai,. Modeling and optimization of unbalanced multi-stage logistic system [J]. Journal of Southeast University (English Edition), 2005, 21 (2): 220-224. [doi:10.3969/j.issn.1003-7985.2005.02.021]
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Modeling and optimization of unbalanced multi-stage logistic system(
)
非平衡多阶段物流系统建模与优化方法
)Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]
- Volumn:
- 21
- Issue:
- 2005 2
- Page:
- 220-224
- Research Field:
- Automation
- Publishing date:
- 2005-06-30
Info
- Title:
- Modeling and optimization of unbalanced multi-stage logistic system
- 非平衡多阶段物流系统建模与优化方法
- Author(s):
- Xu Hang, Xu Rong, Ye Qingtai
- School of Mechanical Engineering, Shanghai Jiaotong University, Shanghai 200030, China
- Keywords:
- logistics; optimization; genetic algorithm; Prüfer number; spanning tree; parameterized interface distribution; unbalanced multi-stage logistic system
- PACS:
- TP18
- DOI:
- 10.3969/j.issn.1003-7985.2005.02.021
- Abstract:
- To decompose an unbalanced multi-stage logistic system to multiple independent single-stage logistic systems, a new notion of parameterized interface distribution is presented.For encoding the logistic pattern on each stage, the Prüfer number is used.With the improved decoding procedure, any Prüfer number produced stochastically can be decoded to a feasible logistic pattern, which can match with the capacities of the nodes of the logistic system.With these two innovations, a new modeling method based on parameterized interface distribution and the Prüfer number coding is put forward.The corresponding genetic algorithm, named as PIP-GA, can find better solutions and require less computational time than st-GA.Although requiring a little more consumption of memory, PIP-GA is still an efficient and robust method in the modeling and optimization of unbalanced multi-stage logistic systems.
- 首先提出了参数化界面分布的新概念, 将一个非平衡多阶段物流系统转化为多个相互独立的单一阶段物流系统, 然后采用Prüfer数对每个阶段上的物流模式进行编码.通过一种改进的解码方法, 任何一个随机产生的Prüfer数都能够被解码为一个与物流系统的节点容量相匹配的可行的物流模式.基于这2点创新, 建立了一种新的基于参数化界面分布和Prüfer数编码的系统建模方法, 相应的遗传算法称为PIP-GA方法.与st-GA方法相比, PIP-GA不但具有更好的优化结果, 而且需要的计算时间更少;虽然所需的存储空间有所增加, PIP-GA仍然是一种有效而稳健的非平衡多阶段物流系统建模与优化方法.
References:
[1] Syarif A, Yun Y S, Gen M.Study on multi-stage logistic chain network:a spanning tree-based genetic algorithm approach [J].Computers and Industrial Engineering, 2002, 43(1, 2):299-314.
[2] Syarif A, Gen M.Hybrid genetic algorithm for production/distribution system in supply chain [J].International Journal of Smart Engineering System Design, 2003, 5(4):289-298.
[3] Gen M, Cheng R.Genetic algorithms and engineering optimization [M].New York:Wiley, 2000.
[4] Gen M, Cheng R, Oren S.Network design techniques using adapted genetic algorithms [J].Advances in Engineering Software, 2001, 32(9):731-744.
[5] Zhou G, Min H, Gen M.The balanced allocation of customers to multiple distribution centers in the supply chain network:a genetic algorithm approach [J].Computers and Industrial Engineering, 2002, 43(1, 2):251-261.
[6] Zhou G, Zhu Y, Weng X, et al.The generalized approaches of genetic algorithms on constrained minimum spanning tree problems [A].In:Proc of World Congr Intelligent Control Autom[C].Piscataway:Institute of Electrical and Electronics Engineers Inc, 2004.2141-2145.
[7] Syarif A, Gen M.Solving exclusionary side constrained transportation problem by using a hybrid spanning tree-based genetic algorithm [J].Journal of Intelligent Manufacturing, 2003, 14(3, 4):389-399.
[8] Zhou G, Gen M.A genetic algorithm approach on tree-like telecommunication network design problem [J].Journal of the Operational Research Society, 2003, 54(3):248-254.
Memo
- Memo:
- Biographies: Xu Hang(1975—), male, graduate;Ye Qingtai(corresponding author), male, professor, yqingtai@online.sh.cn.