Indonesian Journal of Electrical Engineering and Computer Science · 2020 · 10 citations · 17 references
ComputingGeneticsAlgorithmsOptimizationPopulation ImprovementCombinatorial OptimizationEvolutionary ComputationGenetic AlgorithmsHeuristic SearchMetaheuristic OptimizationMutation OperatorsEvolutionary AlgorithmsHybrid Evolutionary AlgorithmsHybrid Genetic AlgorithmsLocal SearchLocal Search AlgorithmsMutationNp-hardnessTraveling Salesman Problem
<span>Robust known the exceedingly famed NP-hard problem in combinatorial optimization is the Traveling Salesman Problem (TSP), promoting the skillful algorithms to get the solution of TSP have been the burden for several scholars. For inquiring global optimal solution, the presented algorithm hybridizes genetic and local search algorithm to take out the uplifted quality results. The genetic algorithm gives the best individual of population by enhancing both cross over and mutation operators while local search gives the best local solutions by testing all neighbor solution. By comparing with the conventional genetic algorithm, the numerical outcomes acts that the presented algorithm is more adequate to attain optimal or very near to it. Problems arrested from the TSP library strongly trial the algorithm and shows that the proposed algorithm can reap outcomes within reach optimal. For more details, please download TEMPLATE HELP FILE from the website.</span>
17
Optimization by Simulated Annealing
Scott Kirkpatrick, C. D. Gelatt, M.P. Vecchi · Science · 1983 · 44.6K citations
Riccardo Poli, James Kennedy, Tim Blackwell · Swarm Intelligence · 2007 · 21.4K citations
Fred Glover · INFORMS Journal on Computing · 1990 · 5.6K citations
Genetic algorithms for the traveling salesman problem
Jean‐Yves Potvin · Annals of Operations Research · 1996 · 397 citations