Return
Glowworm swarm optimization algorithm with topsis for solving multiple objective environmental economic dispatch problem
DOI:10.1016/j.asoc.2014.06.049.png)
Abstract
En 中文
A new glowworm swarm optimization (GSO) algorithm is proposed to find the optimal solution for multiple objective environmental economic dispatch (MOEED) problem. In this proposed approach, technique for order preference similar to an ideal solution (TOPSIS) is employed as an overall fitness ranking tool to evaluate the multiple objectives simultaneously. In addition, a time varying step size is incorporated in the GSO algorithm to get better performance. Finally, to evaluate the feasibility and effectiveness of the proposed combination of GSO algorithm with TOPSIS (GSO-T) approach is examined in four different test cases. Simulation results have revealed the capabilities of the proposed GSO-T approach to find the optimal solution for MOEED problem. The comparison with own coded weighted sum method incorporated GSO (WGSO) and other methods reported in literatures exhibit the superiority of the proposed GSO-T approach and also the results confirm the potential of the proposed GSO-T approach to solve the MOEED problem. (C) 2014 Elsevier B.V. All rights reserved.
Keywords:
Glowworm swarm optimization
TOPSIS
Environmental economic dispatch
Valve point loading effect
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
6.6
Papers:
1.4W
Citations:
4.8W
Organization
Cited Papers
Biogeography based optimization technique for best compromise solution of economic emission dispatch
Environmental/economic power dispatch problem using multi-objective differential evolution algorithm

