Abstract
ASrank has been proposed as an improved version of the ant colony optimisation (ACO) model. However, ASrank includes behaviours that do not exist in the actual biological system and fall into a local solution. To address this issue, we developed ASmulti, a new type of ASrank, in which each agent contributes to pheromone depositions by estimating its rank by interacting with the encountered agents. In this paper, we attempt further improvements in the performance of ASmulti by allowing agents to consider their position in a local hierarchy. Agents in the proposed model (AShierarchy) contribute to pheromone depositions by estimating the consistency between a local hierarchy and global (system) hierarchy. We show that, by using several TSP datasets, the proposed model can find a better solution than ASmulti.
Highlights
Ant colony optimisation (ACO) is a well-known strategy for determining short tours in the travelling salesman problem (TSP) [1]
In ASmulti, the probability of the destination selection determined in the same manner as in ASrank, but a new approach is used for regulating agents who contribute to pheromone deposition. e new method of pheromone update in ASmulti is explained here
We used four TSP datasets: Eil51.tsp (Ncity 51), Berlin52.tsp (Ncity 52), Lin105.tsp (Ncity 105), and Pr124.tsp (Ncity 124). Some of these datasets have often been used for benchmark tests [14, 15]. e TSP datasets used here are classified as symmetric travelling salesman problem wherein the edge length between two cities in the opposite directions is the same
Summary
Ant colony optimisation (ACO) is a well-known strategy for determining short tours in the travelling salesman problem (TSP) [1]. Many ACO models have been developed by extending the ant system (AS) proposed by Dorigo [2,3,4,5,6]. Rank-based ant system (ASrank) is one of the representative models that extend the original AS [7]. Using the pheromone procedure update for exploring simulations, this model finds a solution to the TSP. In ASrank, ant agents are ranked in the order of shorter tour lengths at the end of each tour. The top-ranking agents are allowed to deposit pheromones. Is function improves the convergence of the system by adding pheromones on only the edges toured by top-ranked agents The top-ranking agents are allowed to deposit pheromones. is function improves the convergence of the system by adding pheromones on only the edges toured by top-ranked agents
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