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ACO-ILS-SA opensource

The Ant Colony Optimisation (ACO), Simulated Annealing (SA), and Iterated Local Search (ILS) algorithms are examples of the Operations Research methods used to explore the configuration space of an optimisation problem and arrive at a sub/optimal solution sufficiently quickly. These algorithms are provided in a collection of code titled, "ACO-ILS-SA" used to explore Travelling Salesperson Problem (TSP) like problem instances.


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Release Version Download Link Size md5
1.0 aco-ils-sa-1.0.tar.gz 317K 9c5d16fa5388a71d1d91aed2f256ba37
ANSI C, Serial Software

aco-ils-sa SVN

svn checkout svn://opensource.ihpc.a-star.edu.sg/aco-ils-sa/trunk aco-ils-sa

*If you wish to participate in aco-ils-sa development, please contact the project maintainer.*


The methodology has been derived and extended from published work in the literature as indicate below:

A hybridization using ILS was made to the ACO heuristic to refine the optimality of the solution. Both ILS and ACO are not new, but their hybridization may be new.The perturbation methods used in both SA and ILS are the -Optimality methods, 2-Opt. and 3-Opt. (these are not new), which swap two and three arcs respectively, whilst maintaining tour feasibility: the optimality of the associated solutions is then compared and the more optimal configuration chosen. Please refer to the user guide for detailed information.

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