NDLI: An empirical comparison of five efficient heuristics for Maximal Covering Location Problems

Content Provider	IEEE Xplore Digital Library
Author	Li Xia Ming Xie Weida Xu Jinyan Shao Wenjun Yin Jin Dong
Copyright Year	2009
Description	Author affiliation: IBM China Research Laboratory, Diamond Building, Zhongguancun Software Park, Beijing 100193, China (Li Xia; Ming Xie; Jinyan Shao; Wenjun Yin; Jin Dong) \|\| Department of Automation, Tsinghua University, Beijing 100084, China (Weida Xu)
Abstract	Facility location decision is a critical element in strategic planning for a wide range of public sector and business world. Maximal Covering Location Problem (MCLP) is one of the well-known models for facility location problems. Algorithms to optimally solve this kind of practical operational management problem often suffer from the combinatorial explosion when the system size increases. In these cases, heuristic methods are the only viable alternative. A lot of work has been devoted to the study of heuristics for MCLP. But there lacks a complete comparison of different methods. In this paper, we compare the relative performance of five efficient heuristic methods: Greed-Add, Interchange, Efficient Genetic Algorithm (GA), Efficient Tabu Search (TS), and Efficient Simulated Annealing (SA). The results indicate: Greedy-Add can achieve relatively good solutions in a very short time; GA-based algorithm performs not as successfully as it used to do in most combinatorial problems; and Efficient SA always gets the best solution among all the five algorithms. Thus, in general we may conclude that Efficient SA should often be tried first for this kind of problems.
Starting Page	747
Ending Page	753
File Size	6580928
Page Count	7
File Format	PDF
ISBN	9781424435401
DOI	10.1109/SOLI.2009.5204032
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-07-22
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Automation Operations research Profitability simulated annealing Laboratories maximal covering location problem Strategic planning Educational institutions Explosions Genetic algorithms genetic algorithm Tabu search Simulated annealing Business
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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