Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/30850
Title: | An ant colony optimization based memetic algorithm for the dynamic travelling salesman problem | Authors: | Mavrovouniotis, Michalis Müller, Felipe Martins Yang, Shengxiang |
Major Field of Science: | Natural Sciences | Field Category: | Computer and Information Sciences | Keywords: | Ant colony optimization;Dynamic travelling salesman problem;Local search;Memetic computing | Issue Date: | 11-Jul-2015 | Source: | 16th Genetic and Evolutionary Computation Conference, GECCO 2015, Madrid, Spain, 11 - 15 July 2015 | Conference: | GECCO 2015 - Proceedings of the 2015 Genetic and Evolutionary Computation Conference | Abstract: | Ant colony optimization (ACO) algorithms have proved to be able to adapt for solving dynamic optimization problems (DOPs). The integration of local search algorithms has also proved to significantly improve the output of ACO algorithms. However, almost all previous works consider stationary environments. In this paper, the MAX-MIN Ant System, one of the best ACO variations, is integrated with the unstringing and stringing (US) local search operator for the dynamic travelling salesman problem (DTSP). The best solution constructed by ACO is passed to the US operator for local search improvements. The proposed memetic algorithm aims to combine the adaptation capabilities of ACO for DOPs and the superior performance of the US operator on the static travelling salesman problem in order to tackle the DTSP. The experiments show that the MAX-MIN Ant System is able to provide good initial solutions to US and the proposed algorithm outperforms other peer ACO-based memetic algorithms on different DTSPs. | URI: | https://hdl.handle.net/20.500.14279/30850 | ISBN: | 9781450334723 | DOI: | 10.1145/2739480.2754651 | Rights: | © ACM | Type: | Conference Papers | Affiliation : | De Montfort University Federal University of Santa Maria |
Appears in Collections: | Άρθρα/Articles |
CORE Recommender
SCOPUSTM
Citations
20
26
checked on Mar 14, 2024
Page view(s) 20
90
Last Week
0
0
Last month
3
3
checked on Nov 21, 2024
Google ScholarTM
Check
Altmetric
Items in KTISIS are protected by copyright, with all rights reserved, unless otherwise indicated.