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首页> 外文期刊>Applied Soft Computing >Glowworm swarm optimization algorithm with topsis for solving multiple objective environmental economic dispatch problem
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Glowworm swarm optimization algorithm with topsis for solving multiple objective environmental economic dispatch problem

机译:基于Topsis的萤火虫优化算法解决多目标环境经济调度问题

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摘要

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.
机译:提出了一种新的萤火虫群​​优化算法(GSO),为多目标环境经济调度(MOEED)问题寻找最优解。在此提议的方法中,类似于理想解决方案(TOPSIS)的用于订单偏好的技术被用作总体适应性排名工具,以同时评估多个目标。另外,时变步长已合并到GSO算法中以获得更好的性能。最后,在四个不同的测试案例中,评估了所提出的GSO算法与TOPSIS(GSO-T)方法相结合的可行性和有效性。仿真结果表明,提出的GSO-T方法可以找到MOEED问题的最佳解决方案。与结合了GSO(WGSO)的自身编码加权和方法以及文献中报道的其他方法的比较显示了所提出的GSO-T方法的优越性,并且结果也证实了所提出的GSO-T方法解决MOEED问题的潜力。

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