Glowworm swarm optimization algorithm with topsis for solving multiple objective environmental economic dispatch problem

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.

[1]  Kalyanmoy Deb,et al.  Evolutionary Multi-objective Environmental/Economic Dispatch: Stochastic Versus Deterministic Approaches , 2005, EMO.

[2]  Yong Zhang,et al.  Environmental/economic power dispatch using a hybrid multi-objective optimization algorithm , 2010 .

[3]  Allen J. Wood,et al.  Power Generation, Operation, and Control , 1984 .

[4]  Amir Hossein Gandomi,et al.  Firefly Algorithm for solving non-convex economic dispatch problems with valve loading effect , 2012, Appl. Soft Comput..

[5]  Mousumi Basu,et al.  Economic environmental dispatch using multi-objective differential evolution , 2011, Appl. Soft Comput..

[6]  P. K. Chattopadhyay,et al.  Solving economic emission load dispatch problems using hybrid differential evolution , 2011, Appl. Soft Comput..

[7]  Ugur Güvenc,et al.  Combined economic and emission dispatch solution using gravitational search algorithm , 2012, Sci. Iran..

[8]  Debasish Ghose,et al.  Detection of multiple source locations using a glowworm metaphor with applications to collective robotics , 2005, Proceedings 2005 IEEE Swarm Intelligence Symposium, 2005. SIS 2005..

[9]  Serdar Özyön,et al.  Charged system search algorithm for emission constrained economic power dispatch problem , 2012 .

[10]  Wen-Hwa Liao,et al.  A sensor deployment approach using glowworm swarm optimization algorithm in wireless sensor networks , 2011, Expert Syst. Appl..

[11]  Prakash Kumar Hota,et al.  Economic emission load dispatch through fuzzy based bacterial foraging algorithm , 2010 .

[12]  Morteza Yazdani,et al.  A state-of the-art survey of TOPSIS applications , 2012, Expert Syst. Appl..

[13]  P. Aravindhababu,et al.  Biogeography based optimization technique for best compromise solution of economic emission dispatch , 2012, Swarm Evol. Comput..

[14]  M. A. Abido Environmental/economic power dispatch using multiobjective evolutionary algorithms , 2003 .

[15]  D. P. Kothari,et al.  Stochastic economic emission load dispatch , 1993 .

[16]  P. K. Chattopadhyay,et al.  Hybrid differential evolution with biogeography-based optimization algorithm for solution of economic emission load dispatch problems , 2011, Expert Syst. Appl..

[17]  Debasish Ghose,et al.  Glowworm swarm optimisation: a new method for optimising multi-modal functions , 2009, Int. J. Comput. Intell. Stud..

[18]  Ferial El-Hawary,et al.  A summary of environmental/economic dispatch algorithms , 1994 .

[19]  Debasish Ghose,et al.  Glowworm swarm optimization for simultaneous capture of multiple local optima of multimodal functions , 2009, Swarm Intelligence.

[20]  J. W. Lamont,et al.  Emission dispatch models and algorithms for the 1990s , 1995 .

[21]  Mohammad Ali Abido,et al.  Multiobjective evolutionary algorithms for electric power dispatch problem , 2006, IEEE Transactions on Evolutionary Computation.

[22]  Narayana Prasad Padhy,et al.  Comparison and application of evolutionary programming techniques to combined economic emission dispatch with line flow constraints , 2003 .

[23]  S. Hemamalini,et al.  Emission constrained economic dispatch with valve-point effect using particle swarm optimization , 2008, TENCON 2008 - 2008 IEEE Region 10 Conference.

[24]  H.C.S. Rughooputh,et al.  Elitist multiobjective evolutionary algorithm for environmental/economic dispatch , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[25]  Yaonan Wang,et al.  Environmental/economic power dispatch problem using multi-objective differential evolution algorithm , 2010 .

[26]  M. A. Abido,et al.  Multiobjective particle swarm optimization for environmental/economic dispatch problem , 2009 .

[27]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[28]  T. Jayabarathi,et al.  Evolutionary programming techniques for different kinds of economic dispatch problems , 2005 .

[29]  Bin Wu,et al.  The improvement of glowworm swarm optimization for continuous optimization problems , 2012, Expert Syst. Appl..

[30]  G. Sheblé,et al.  Genetic algorithm solution of economic dispatch with valve point loading , 1993 .

[31]  Sakti Prasad Ghoshal,et al.  Solution of combined economic and emission dispatch problems of power systems by an opposition-based harmony search algorithm , 2012 .