A study of permutation crossover operators on the traveling salesman problem
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
ASPARAGOS an asynchronous parallel genetic optimization strategy
Proceedings of the third international conference on Genetic algorithms
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
AllelesLociand the Traveling Salesman Problem
Proceedings of the 1st International Conference on Genetic Algorithms
Proceedings of the 14th International conference on Industrial and engineering applications of artificial intelligence and expert systems: engineering of intelligent systems
A nested genetic algorithm for optimal container pick-up operation scheduling on container yards
ICNC'06 Proceedings of the Second international conference on Advances in Natural Computation - Volume Part I
Hi-index | 0.00 |
In Genetic and Evolutionary Algorithms (GEAs) one is faced with a given number of parameters, whose possible values are coded in a binary alphabet. With Order Based Representations (OBRs) the genetic information is kept by the order of the genes and not by its value. The application of OBRs to the Traveling Salesman Problem (TSP) is a well known technique to the GEA community. In this work one intends to show that this coding scheme can be used as an indirect representation, where the chromosome is the input for the decoder. The behavior of the GEA's operators is compared under benchmarks taken from the Combinatorial Optimization arena.