Title :
Iterated Local Search with Guided Mutation
Author :
Zhang, Qingfu ; Sun, Jianyong
Author_Institution :
Univ. of Essex, Colchester
Abstract :
Guided mutation uses the idea of estimation of distribution algorithms to improve conventional mutation operators. It combines global statistical information and the location information of good individual solutions for generating new trial solutions. This paper suggests using guided mutation in iterative local search. An experimental comparison between a conventional iterated local search (CILS) and an iterated local search with guided mutation has been conducted on four classes of the test instances of the quadratic assignment problem.
Keywords :
iterative methods; search problems; distribution algorithms estimation; global statistical information; guided mutation; iterated local search; quadratic assignment problem; Algorithm design and analysis; Computer science; Data mining; Electronic design automation and methodology; Evolutionary computation; Genetic mutations; Heuristic algorithms; Iterative algorithms; Sun; Testing;
Conference_Titel :
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9487-9
DOI :
10.1109/CEC.2006.1688410
