About cookies on this site Our websites require some cookies to function properly (required). In addition, other cookies may be used with your consent to analyze site usage, improve the user experience and for advertising. For more information, please review your options. By visiting our website, you agree to our processing of information as described in IBM’sprivacy statement. To provide a smooth navigation, your cookie preferences will be shared across the IBM web domains listed here.
Publication
WSC 2009
Conference paper
Efficient optimization of maximal covering location problems using extreme value estimation
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. ©2009 IEEE.