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Abstract—This study proposes a new Ant Colony Op-timization (method; ACO) with Intelligent and Dull Ants (IDACO). In IDACO algorithm, two kinds of ants coexist: intelligent ants and dull ants. IDACO algorithm is nearer to the real ant colony than the standard ACO algorithm. We apply IDACO to Traveling Salesman Problems (TSPs) and confirm that IDACO obtains more effective results than the standard ACO which consists of only the intelligent ants. 1
A number of extensions of Ant System, the first ant colony optimization (ACO) algorithm, were propos...
Recently, a number of algorithms inspired by the foraging behavior of ant colonies have been applied...
Swarm intelligence is a relatively new approach to problem solving that takes inspiration from the s...
timization with Intelligent and Dull Ants (GIDACO). In the GIDACO algorithm, two kinds of ants coexi...
Ant colony optimization (ACO) is an evaluational optimization algorithm inspired by pheromone effect...
Abstract: Ant Colony Optimization (ACO) a nature-inspired metaheuristic algorithm has been successfu...
Ant Colony Optimization (ACO) has been applied successfully in solving the Traveling Salesman Proble...
Abstract. Ant Colony Optimization (ACO) has been applied successfully in solving the Traveling Sales...
Traveling salesman problem (TSP) is an optimization problem in determining the optimal route of a nu...
Ant colony optimization (ACO) algorithms are a recently developed, population-based approach which h...
A number of extensions of Ant System, the first ant colony optimization (ACO) algorithm, were pro...
warm intelligence is a relative-ly new approach to problem solving that takes inspiration from the s...
Ant Colony Optimization (ACO) [31, 32] is a recently proposed metaheuristic ap-proach for solving ha...
Ant Colony Optimization (ACO) is a heuristic algorithm which has been proven a successful technique ...
In latest years, Optimization Algorithms have been one of the most interesting applications that can...
A number of extensions of Ant System, the first ant colony optimization (ACO) algorithm, were propos...
Recently, a number of algorithms inspired by the foraging behavior of ant colonies have been applied...
Swarm intelligence is a relatively new approach to problem solving that takes inspiration from the s...
timization with Intelligent and Dull Ants (GIDACO). In the GIDACO algorithm, two kinds of ants coexi...
Ant colony optimization (ACO) is an evaluational optimization algorithm inspired by pheromone effect...
Abstract: Ant Colony Optimization (ACO) a nature-inspired metaheuristic algorithm has been successfu...
Ant Colony Optimization (ACO) has been applied successfully in solving the Traveling Salesman Proble...
Abstract. Ant Colony Optimization (ACO) has been applied successfully in solving the Traveling Sales...
Traveling salesman problem (TSP) is an optimization problem in determining the optimal route of a nu...
Ant colony optimization (ACO) algorithms are a recently developed, population-based approach which h...
A number of extensions of Ant System, the first ant colony optimization (ACO) algorithm, were pro...
warm intelligence is a relative-ly new approach to problem solving that takes inspiration from the s...
Ant Colony Optimization (ACO) [31, 32] is a recently proposed metaheuristic ap-proach for solving ha...
Ant Colony Optimization (ACO) is a heuristic algorithm which has been proven a successful technique ...
In latest years, Optimization Algorithms have been one of the most interesting applications that can...
A number of extensions of Ant System, the first ant colony optimization (ACO) algorithm, were propos...
Recently, a number of algorithms inspired by the foraging behavior of ant colonies have been applied...
Swarm intelligence is a relatively new approach to problem solving that takes inspiration from the s...
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