2011/12/01 by Camelia-M. Pintea, Camelia Chira, D. Dumitrescu +1 · 24 citations
Computer Science · Engineering · Mathematics · #ANT #Ant colony #Ant colony optimization algorithms #Artificial intelligence #Computer network #Computer science #Engineering #Mathematical optimization #Mathematics #Metaheuristic Optimization Algorithms Research #Optimization and Packing Problems #Population #Routing (electronic design automation) #Sensitivity (control systems) #Vehicle Routing Optimization Methods #Vehicle routing problem #cs.AI #cs.NE #msc:68T20
paper · pdf · open access · doi:10.15837/ijccc.2011.4.2098
published in International Journal of Computers Communications & Control 6(4), 731 (Agora University) · 5 pages
openalex publication_date 2011/12/01 · arxiv created 2012/08/27 · arxiv updated 2020/07/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
The idea of sensitivity in ant colony systems has been exploited in hybrid ant-based models with promising results for many combinatorial optimization problems. Heterogeneity is induced in the ant population by endowing individual ants with a certain level of sensitivity to the pheromone trail. The variable pheromone sensitivity within the same population of ants can potentially intensify the search while in the same time inducing diversity for the exploration of the environment. The performance of sensitive ant models is investigated for solving the generalized vehicle routing problem. Numerical results and comparisons are discussed and analysed with a focus on emphasizing any particular aspects and potential benefits related to hybrid ant-based models.