A hybrid algorithm using a genetic algorithm and multiagent reinforcement learning heuristic to solve the traveling salesman problem.
Mir Mohammad AlipourSeyed Naser RazaviMohammad-Reza Feizi-DerakhshiMohammad Ali BalafarPublished in: Neural Comput. Appl. (2018)
Keyphrases
- hybrid algorithm
- traveling salesman problem
- ant colony optimization
- combinatorial optimization
- simulated annealing
- nonlinear integer programming
- genetic algorithm
- tabu search
- metaheuristic
- multiagent reinforcement learning
- benchmark instances
- ant colony optimization algorithm
- optimal solution
- traveling salesman
- particle swarm optimization
- particle swarm optimization pso
- satisfy the triangle inequality
- mathematical programming
- crossover operator
- vehicle routing problem
- swarm intelligence
- nature inspired
- ant colony algorithm
- differential evolution
- aco algorithm
- job shop scheduling problem
- optimization problems
- solution quality
- multi agent
- multiagent systems
- benchmark problems
- scheduling problem
- optimization method
- search algorithm
- evolutionary algorithm
- multi objective
- search procedure
- routing problem
- cooperative
- genetic algorithm ga
- fitness function
- special case
- stochastic games