NDLI: Genetic algorithm and local search comparison for solving bi-objective p-Median problem

Content Provider	IEEE Xplore Digital Library
Author	Tangpattanakul, P.
Copyright Year	2015
Description	Author affiliation: Geo-Inf. & Space Technol. Dev. Agency (Public Organ.), Bangkok, Thailand (Tangpattanakul, P.)
Abstract	This paper presents two algorithms, which are a nondominated sorting genetic algorithm II (NSGA-II) and an indicator-based multi-objective local search (IBMOLS), for solving a bi-objective p-Median problem. The bi-objective p-Median problem is a problem of finding p location points to install facilities from a set of m candidates. This problem considers two objectives: minimizing the sum of the distances from each customer to the nearest facility and minimizing the sum of the costs to install each facility in the selected location points. NSGA-II and IBMOLS are efficient algorithms in the area of multi-objective optimization. Experiments are conducted on generated instances. Hypervolume values of the approximate Pareto fronts are computed and the obtained results from IBMOLS and NSGA-II are compared.
Starting Page	1
Ending Page	5
File Size	746126
Page Count	5
File Format	PDF
e-ISBN	9781467369022
DOI	10.1109/ICIEV.2015.7334052
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-06-15
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Sociology Search problems Statistics Biological cells Optimization Genetic algorithms Sorting
Content Type	Text
Resource Type	Article

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