2012/08/31 by Camelia-M. Pintea, Camelia M. Pintea, Gloria Cerasela Crisan +1
Computer Science · Engineering · #Ant colony #Ant colony optimization algorithms #Extremal optimization #Metaheuristic Optimization Algorithms Research #Ring (chemistry) #Routing (electronic design automation) #Scale (ratio) #Slime Mold and Myxomycetes Research #Travelling salesman problem #Vehicle Routing Optimization Methods #acm:68T10 #acm:68T20 #acm:90C27 #cs.AI #msc:68T10 #msc:68T20 #msc:90C27
paper · pdf · doi:10.4018/jitr.2012100101
published as J Information Technology Research 5(4): 1-13 (2012) · 8 pages, 1 figure; accepted J. Information Technology Research
openalex publication_date 2012/10/01 · arxiv created 2012/10/10 · openalex created_date 2016/06/24 · arxiv updated 2020/07/28 · openalex updated_date 2026/08/05
The current paper introduces a new parallel computing technique based on ant colony optimization for a dynamic routing problem. Ant Colony Optimization is a metaheurisitc that is able to solve large scale optimization problems. In the dynamic traveling salesman problem, the distances between cities as travel times are no longer fixed. The new technique uses a parallel model for a problem variant that allows a slight movement of nodes within their neighborhoods. The algorithm is tested with success on several large data sets. The paper concludes with a discussion of the results provided by both the sequential and parallel approaches and calls for further research on the subject.