In this paper, an improved ant colony optimization (ICMPACO) algorithm based on the multi-
population strategy, co-evolution mechanism, pheromone updating strategy, and …

Ant Colony Optimization (ACO) is a widely applied meta-heuristic algorithm. Little
researches focused on the candidate selection mechanism, which was developed based on …

Traveling salesman problem (TSP) is one typical combinatorial optimization problem. Ant
colony optimization (ACO) is useful for solving discrete optimization problems whereas the …

In this paper, an effective improved co-evolution ant colony optimisation (MSICEAO)
algorithm is presented to solve complex optimisation problem. In the MSICEAO, the multi …

As one suitable optimization method implementing computational intelligence, ant colony
optimization (ACO) can be used to solve the traveling salesman problem (TSP). However …

Ant colony optimization (ACO) algorithm is a recent meta-heuristic method inspired by the
behavior of real ant colonies. The algorithm uses parallel computation mechanism and …

Metaheuristics are a type of approximate optimization algorithms for solving hard and
complex problems in science and engineering [1]. They can be defined as algorithm …

In this paper, a parameter adaptation-based ant colony optimization (ACO) algorithm based
on particle swarm optimization (PSO) algorithm with the global optimization ability, fuzzy …

Mutated ant colony optimization (MACO) algorithm is proposed by introducing the mutation
mechanism to the ACO algorithm, and is applied to the traveling salesman problem (TSP) …

Path planning problems have attracted the interest of more and more researchers due to its
widespread existence in recent years. For example, express delivery and food delivery …