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

• A new glowworm swarm optimization (GSO) algorithm with TOPSIS is proposed and applied to multiple objective environmental economic dispatch problem.
• In the proposed GSO with TOPSIS (GSO–T) approach the TOPSIS is employed as an overall fitness evaluation tool.
• The proposed GSO–T approach is implemented on four different test cases.
• Results obtained by the GSO–T approach are compared with own coded weighted sum method incorporated GSO (WGSO) and also with other methods reported by various researchers.
• The results conclude that the proposed GSO–T approach produce better results over other algorithms. It can be applied to a wide range of optimization problems.

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.

Figure optionsDownload as PowerPoint slide