Application of Latin hypercube sampling in the immune genetic algorithm for solving the maximum clique problem

Authors:
Zhou Benda;Chen Minghua
Affiliations:
Dept. of Mathematics & Physics, West Anhui University, Lu'an, China;Dept. of Mathematics & Physics, West Anhui University, Lu'an, China
Venue:
AICI'10 Proceedings of the 2010 international conference on Artificial intelligence and computational intelligence: Part II
Year:
2010

Citing 4
Cited 0

Large sample properties of simulations using latin hypercube sampling

Technometrics
Optimized Crossover-Based Genetic Algorithms for the Maximum Cardinality and Maximum Weight Clique Problems

Journal of Heuristics
A hybrid heuristic for the maximum clique problem

Journal of Heuristics
Dynamic local search for the maximum clique problem

Journal of Artificial Intelligence Research

Quantified Score

Hi-index	0.00

Visualization

Abstract

Based on Latin Hypercube Sampling method, the crossover operation in GA is redesigned; combined with immune mechanism, chromosome concentration is defined and clonal selection strategy is designed, thus an Immune Genetic Algorithm is given based on Latin Hypercube Sampling for solving the Maximum Clique Problem in this paper. The examples shows the new algorithm in solution quality, convergence speed, and other indicators is better than the classical genetic algorithm and good point set genetic algorithm. On the other hand, the new algorithm is not inferior to such classical algorithms as dynamic local search, and it got better solutions to some examples.