Efficient optimization of maximal covering location problems using extreme value estimation

Authors:
Li Xia;Wenjun Yin;Weida Xu;Ming Xie;Jinyan Shao
Affiliations:
IBM China Research Laboratory, Zhongguancun Software Park, Beijing, P. R. China;IBM China Research Laboratory, Zhongguancun Software Park, Beijing, P. R. China;Tsinghua University, Beijing, P. R. China;IBM China Research Laboratory, Zhongguancun Software Park, Beijing, P. R. China;IBM China Research Laboratory, Zhongguancun Software Park, Beijing, P. R. China
Venue:
Winter Simulation Conference
Year:
2009

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Abstract

Facility location decision is a critical element in strategic planning for a wide range of public sectors and business world. Maximal Covering Location Problem is one of the well-known models for facility location problems. Considering its NP-hard nature, numerous efforts have been devoted to the development of intelligent algorithms for this problem. In order to evaluate the quality of a given solution, we integrate k-interchange heuristic and extreme value theory to statistically estimate the upper bound of the global optimal objective value. Based on this statistical bound, a new simulated annealing algorithm is proposed to solve the maximal covering location problems. Computational results show that the proposed algorithm can obtain better near optimal solutions than the existing algorithms.