DocumentCode
419023
Title
A genetic algorithm applied to graph problems involving subsets of vertices
Author
Alkhalifah, Yaser ; Wainwright, Roger L.
Author_Institution
Dept. of Math. & Comput. Sci., Tulsa Univ., OK, USA
Volume
1
fYear
2004
fDate
19-23 June 2004
Firstpage
303
Abstract
Many graph problems seek subsets of their vertices that maximize or minimize objective functions on the vertices. Among these are the capacitated p-median problem, the geometric connected dominating set problem, the capacitated k-center problem, and the traveling tourist problem. Prior genetic algorithms research in this area applied a simple mutation of an allele by random replacement. Recently an enhanced operator called hypermutation was developed, proving to be very effective for solving the capacitated p-median problem. We propose a GA with a new heuristic called the nearest four neighbors heuristic (N4N) for solving graph problems requiring a subset of vertices. It is an extension of the hypermutation operator. Genetic algorithms that use each of these three mutation operators (simple, hypermutation, N4N) are applied to instances of the four graph-subset problems listed above. Results show that our N4N heuristic obtained superior results compared to the hypermutation and the simple mutation operators in every test case.
Keywords
genetic algorithms; graph theory; travelling salesman problems; N4N heuristic; capacitated k-center problem; capacitated p-median problem; genetic algorithm; geometric connected dominating set problem; graph problem; graph-subset problems; hypermutation operator; mutation operators; nearest four neighbors heuristic; objective function maximization; objective function minimization; random replacement; traveling tourist problem; vertex subsets; Algorithm design and analysis; Educational institutions; Genetic algorithms; Genetic mutations; Processor scheduling; Telecommunication computing; Testing; Transportation;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2004. CEC2004. Congress on
Print_ISBN
0-7803-8515-2
Type
conf
DOI
10.1109/CEC.2004.1330871
Filename
1330871
Link To Document