An Evolutionary Approach to the Zero/One Knapsack Problem: Testing Ideas from Biology
The transposition mechanism, widely studied in previous publications, showed that when used instead of the standard crossover operators, allows the genetic algorithm to achieve better solutions. Nevertheless, all the studies made concerning this mechanism always focused the domain of function optimization. In this paper, we present an empirical study that compares the performances of the transposition-based GA and the classical GA solving the 0/1 knapsack problem. The obtained results show that, just like in the domain of function optimization, transposition is always superior to crossover.
KeywordsGenetic Algorithm Penalty Function Knapsack Problem Genetic Operator Binary String
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