By Topic

Diversity-guided bilateral objective function and its application to optimal planning of cogeneration

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Chen-Yu Chen ; Innovative DigiTech-Eeabled Applic. & Services Inst., Inst. for Inf. Ind., Kaohsiung, Taiwan ; Fu-Chi Chen

The purposes of our work was to design an improved particle swarm optimization (PSO) framework that is capable of wider search area and better fitness values by diversity-guided bilateral objective function. To address the problems of premature convergence of existing PSO techniques, an improved PSO framework have been proposed, consisting of bilateral objective function (BOF). The BOF was developed based on both smaller cost value (minimized) and bigger distribution (diversity-guided) of individuals. Instead of using only cost value down for the objective function as in the case of the conventional optimization techniques, the proposed PSO framework employs both minimized cost value and promoted solution search ability by exploring more wider search space. The global optimum was obtained easier after the combination of bilateral objective function, especially for complex test functions. The proposed algorithm has been demonstrated with a significantly improvement for cost value in couples of test functions.

Published in:

System Science and Engineering (ICSSE), 2010 International Conference on

Date of Conference:

1-3 July 2010