Application of multi objective evolutionary programming to combined economic emission dispatch problem

被引：9
作者：
Jeyakumar, D. N. [1 ]
Venkatesh, P. [2 ]
Lee, Kwang. Y. [2 ]
机构：
[1] PSNA Coll Engn, Dept Elect & Elect Engn, Dindigul, India
[2] Univ Penn, Dept Elect Engn, University Pk, PA 16802 USA
来源：
2007 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-6 | 2007年
关键词：
combined economic emission dispatch; evolutionary programming; non-dominated solution; Pareto optimal solutions;
D O I：
10.1109/IJCNN.2007.4371122
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper describes a new Multi-Objective Evolutionary Programming (MOEP) method to solve the Combined Economic Emission Dispatch (CEED) problem. CEED is a multi-objective optimization problem by considering the fuel cost and emission as the objectives. It is converted into single objective optimization problem using weighted sum method. Hence the MOEP is proposed by employing the non-dominated solution ranking as selection mechanism for the bio-objective CEED problem. The developed algorithm is tested for a three-unit and a six-unit system. The results demonstrate the capabilities of the proposed approach to generate well-distributed Pareto optimal solutions of the multi-objective CEED problem in a single run.
引用
收藏
页码：1162 / +
页数：2
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