원문정보
초록
영어
Internet is changing customers’ consumption patterns and the manufactures’ sale model. With the development of the computer network technology and the electronic commerce, more and more firms establish the electronic sale channel and get great profits. The huge supply chain network is established through the new idea and the technology. In this paper, we propose an improved local search algorithm- clustering local search algorithm (CLSA) to solve the hybrid location problem. We apply this method to distribution center location model and get the optimal solution. Result shows that this method can avoid the exponential explosion and get a good solution. In numerical analysis, we compare this method with simulated annealing method and ant searching algorithm. The numerical analysis demonstrates that this CLSA method not only classifies simply and flexibly, but also has the characteristic of fast search speed and small search space.
목차
1. Introduction
2 The Correlated Conditions to Establish the Location Model
2.1. Assumptions
2.2 The Parameters of the Model
2.3 The Decision Variables
2.4 The Location Model
3. The Improved Local Search Algorithm CLSA (Clustering Local Search Algorithm)
3.1 The Solution Description of the Improved Local Search Algorithm CLSA
3.2 The Density Weighted Fuzzy c Means Clustering Method
3.3 Constructing the Initial Solution Based on the Scanning and the Iterative Method
3.4 The Local Search Algorithm
4. Numerical Analysis
4.1 Set Partitioning
4.2 Reclassification Adjustment
4.3. Comparison of Other Algorithms (Simulated Annealing Method, Ant Algorithm)
5. Conclusion
Acknowledgments
References