Integer and combinatorial optimization
Integer and combinatorial optimization
Tackling Real-Coded Genetic Algorithms: Operators and Tools for Behavioural Analysis
Artificial Intelligence Review
Development of a Parametric Generating Procedure for Integer Programming Test Problems
Journal of the ACM (JACM)
Genetic Algorithms and Grouping Problems
Genetic Algorithms and Grouping Problems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
An Empirical Comparison of Selection Methods in Evolutionary Algorithms
Selected Papers from AISB Workshop on Evolutionary Computing
Genetic Algorithms and Neighbourhood Search
Selected Papers from AISB Workshop on Evolutionary Computing
A naive genetic approach for non-stationary constrained problems
Soft Computing - A Fusion of Foundations, Methodologies and Applications
The gambler's ruin problem, genetic algorithms, and the sizing of populations
Evolutionary Computation
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Formation of hamming cliff hampers the progress of genetic algorithm in seemingly deceptive problems. We demonstrate through an analysis of neighbourhood search capabilities of the mutation operator in genetic algorithm that the problem can somtimes be overcome through proper genetic coding. Experiments have been conducted on a 4-bit deceptive function and the pure-integer programming problem. The integer-coded genetic algorithm performs better and requires less time than the binary-coded genetic algorithm in these problems.