Solving Dynamic Constraint Single Objective Functions using a Nature Inspired Technique

Dewan, Hrishikesh and Nayak, Raksha B (2014) Solving Dynamic Constraint Single Objective Functions using a Nature Inspired Technique. In: 5th International Conference on Information Science and Applications (ICISA), MAY 06-09, 2014, Seoul, SOUTH KOREA.

PDF int_con_inf_sci_app_2014.pdf - Published Version Restricted to Registered users only Download (321kB) | Request a copy

Abstract

We present in this paper a new algorithm based on Particle Swarm Optimization (PSO) for solving Dynamic Single Objective Constrained Optimization (DCOP) problems. We have modified several different parameters of the original particle swarm optimization algorithm by introducing new types of particles for local search and to detect changes in the search space. The algorithm is tested with a known benchmark set and compare with the results with other contemporary works. We demonstrate the convergence properties by using convergence graphs and also the illustrate the changes in the current benchmark problems for more realistic correspondence to practical real world problems.

Item Type:	Conference Proceedings
Series.:	International Conference on Information Science and Applications
Additional Information:	Copyright for this article belongs to the IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Department/Centre:	Division of Electrical Sciences > Computer Science & Automation
Date Deposited:	18 Jan 2015 06:42
Last Modified:	18 Jan 2015 06:42
URI:	http://eprints.iisc.ac.in/id/eprint/50694

Actions (login required)

View Item