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GECCO
2004
Springer
15 years 3 months ago
How to Overcome the Equivalent Mutant Problem and Achieve Tailored Selective Mutation Using Co-evolution
The use of Genetic Algorithms in evolution of mutants and test cases offers new possibilities in addressing some of the main problems of mutation testing. Most specifically the p...
Konstantinos Adamopoulos, Mark Harman, Robert M. H...
ICNSC
2008
IEEE
15 years 4 months ago
Multiple Sequence Alignment Based on Genetic Algorithms with Reserve Selection
— This paper presents an approach to the multiple sequence alignment (MSA) problem by applying genetic algorithms with a reserve selection mechanism. MSA is one of the most funda...
Yang Chen, Jinglu Hu, Kotaro Hirasawa, Songnian Yu
CEC
2008
IEEE
15 years 4 months ago
A parallel surrogate-assisted multi-objective evolutionary algorithm for computationally expensive optimization problems
Abstract— This paper presents a new efficient multiobjective evolutionary algorithm for solving computationallyintensive optimization problems. To support a high degree of parall...
Anna Syberfeldt, Henrik Grimm, Amos Ng, Robert Ivo...
CEC
2008
IEEE
15 years 4 months ago
Correlation clustering based on genetic algorithm for documents clustering
—Correlation clustering problem is a NP hard problem and technologies for the solving of correlation clustering problem can be used to cluster given data set with relation matrix...
Zhenya Zhang, Hongmei Cheng, Wanli Chen, Shuguang ...
GECCO
2006
Springer
192views Optimization» more  GECCO 2006»
15 years 1 months ago
Optimising cancer chemotherapy using an estimation of distribution algorithm and genetic algorithms
This paper presents a methodology for using heuristic search methods to optimise cancer chemotherapy. Specifically, two evolutionary algorithms - Population Based Incremental Lear...
Andrei Petrovski, Siddhartha Shakya, John A. W. Mc...