Name
Abstract | ||
|---|---|---|
In this paper, on the basis of the original genetic algorithm, an improved genetic algorithm for the Traveling Salesman Problem (TSP) is proposed. Firstly, the diversity of species is ensured by amending the calculation method of the individual fitness. Secondly, the mutation operator is improved by the combination of shift mutation and insertion mutation. Before the crossover, the operator checks whether the degradation phenomenon will occur. Finally, experimental results further determine that above improvements provide a significant effect for solving the TSP. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/ICNC.2013.6818008 | ICNC |
Keywords | Field | DocType |
combinatorial problem,optimization,genetic algorithm,traveling salesman problem,individual fitness calculation method,travelling salesman problems,tsp,specie diversity,traveling salesman problem solving,improved genetic algorithm,computational complexity,mutation operator improvement,biological evolution,genetic algorithms,shift mutation,computational model,darwinian genetic selection,insertion mutation,statistics,sociology,convergence,organisms | Bottleneck traveling salesman problem,Genetic operator,Computer science,Artificial intelligence,Christofides algorithm,Genetic algorithm,Chromosome (genetic algorithm),Mathematical optimization,Crossover,Algorithm,Greedy algorithm,2-opt,Machine learning | Conference |
Citations | PageRank | References |
1 | 0.41 | 0 |
Authors | ||
1 | ||