KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/123456789/1

Browse

Settings

Author: search.filters.author.Wardkein, ParamoteSubject: search.filters.subject.Ant colony optimization

Search Results

Now showing 1 - 2 of 2
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Reliability optimization of topology communication network design using an improved ant colony optimization
    (2009-09-01)
    Watcharasitthiwat, Kanyapat
    ;
    Wardkein, Paramote
    Network design problem is a well-known NP-hard problem which involves the selection of a subset of possible links or a network topology in order to minimize the network cost subjected to the reliability constraint. To overcome the problem, this paper proposes a new efficiency algorithm based on the conventional ant colony optimization (ACO) to solve the communication network design when considering both economics and reliability. The proposed method is called improved ant colony optimizations (IACO) which introduces two addition techniques in order to improve the search process, i.e. neighborhood search and re-initialization process. To show its efficiency, IACO is applied to test with three different topology network systems and its results are compared with those obtained results from the conventional approaches, i.e. genetic algorithm (GA), tabu search algorithm (TSA) and ACO. Simulation results, obtained these test problems with various constraints, shown that the proposed approach is superior to the conventional algorithms both solution quality and computational time. © 2009 Elsevier Ltd. All rights reserved.
  • Loading...
    Thumbnail Image
    Some of the metrics are blocked by your 
    consent settings
    Item type:Publication,
    Topological communication network design using ant colony optimization
    (2005-01-01)
    Premprayoon, Patomporn
    ;
    Wardkein, Paramote
    In this paper, Ant Colony Optimization (ACO) is proposed to solve the optimal telecommunication networks design considering both economics and reliability. ACQ is a new cooperative agent approach, which is inspired by the observation or the behaviors of real ant colonies on the topic of ant trial formation and foraging methods. In the ACO, a set of cooperating agents called "ants" cooperates to find good solution. The advantages of ACO are parallel search and optimization capabilities. This approach is interested on the model of the reality telecommunication network. Simulation results on multiple test problems with various degrees of constraint show that this approach has high efficiency and is superior to the conventional Tabu Search algorithm (TSA).