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Integrated use of soft computing and clustering for capacitated clustering single-facility location problem with one-time delivery
Conference paper

Integrated use of soft computing and clustering for capacitated clustering single-facility location problem with one-time delivery

Yunzhi Jiang, Wei-Chang Yeh, Chyh-Ming Lai, Hsiu-Hao Liu, Che-Hou Yeh, Yuk Ying Chung and Jsen-Shung Lin
2016 IEEE Congress on Evolutionary Computation, CEC 2016, pp.2701-2705
11/2016

Abstract

Capacitated Clustering Location Problem (CCP) K-harmonic Means (KHM) Simplified Swarm Optimization Traveling Salesman Problem (TSP) Artificial Intelligence Modeling and Simulation Computer Science Applications Control and Optimization
How to setup the distribution centers (DC) is not only a general issue but also a quite profound knowledge in real world. This problem called capacitated clustering location problem (CCP), then the previous literature, the target of the CCP is to minimize the sum of distances from each DC to all customers in their cluster. However, some types of the company shipping are different from the above. The DC must ship goods to all customers in its cluster in a cycle time. This delivery way called 'one-time delivery' and it can be modeled as Travelling Salesman Problem (TSP). In order to solve this practical problem, a hybrid algorithm, Simplified Swarm Optimization combining with K-harmonic means (SSOKHM) is proposed in this paper for the CCP and using greedy algorithm for the TSP to obtain the minimize shipping costs. Proposed method is applied to several facility location problems from OR library. Numerical results show that the SSOKHM performance is better than using other hybrid clustering algorithms in terms of shipping costs. Finally, we embed the exchange local search for each algorithm. The results are presented that this inspection mechanism can enhance the performance and demonstrate the usefulness in CCP.

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