Title :
An evolutionary algorithm for the T-constrained variation of Minimum Hitting Set problem
Author :
Cutello, V. ; Mastriani, E. ; Pappalardo, F.
Author_Institution :
Dept. of Math. & Comput. Sci., Catania Univ., Italy
Abstract :
We propose an evolutionary algorithm to approximate optimal solutions to instances of the T-constrained variation of the Minimum Hitting Set Problem. The base problem, Minimum Hitting Set, is a well known 𝒩𝒫-complete problem. Our genetic algorithm will use the idea of viruses which infect chromosomes and change one of their bits. A special dynamic fitness function has been also used to improve overall performance
Keywords :
computational complexity; genetic algorithms; set theory; Minimum Hitting Set problem; Minimum Set Cover; NP complete problem; T-constrained variation; chromosomes; combinatorial problems; dynamic fitness function; evolutionary algorithm; genetic algorithm; optimal solution approximation; performance; viruses; Biological cells; Computer science; Evolutionary computation; Genetic algorithms; Genetic mutations; Mathematics; NP-complete problem; Performance evaluation; Polynomials; Viruses (medical);
Conference_Titel :
Evolutionary Computation, 2002. CEC '02. Proceedings of the 2002 Congress on
Conference_Location :
Honolulu, HI
Print_ISBN :
0-7803-7282-4
DOI :
10.1109/CEC.2002.1006262
