Article ID Journal Published Year Pages File Type
4944909 Information Sciences 2016 37 Pages PDF
Abstract
Recently Multi-Objective Improved Teaching-Learning-Based-Optimization algorithm (MO-ITLBO) has been proposed to solve complex multi-objective optimization problems and has been shown to be competitive against various other state-of-the-art algorithms. The algorithm was demonstrated on the constrained and unconstrained optimization problems of CEC 2009 and was reported to have shown impressive results. However, some critical steps in the algorithm have not been adequately described, and these have become major impediments even for the implementation of MO-ITLBO. In this note, we have explained all such issues which need to be convincingly addressed so that independent researchers could evaluate and use MO-ITLBO for various other applications. Also, two variants of MO-ITLBO have been suggested whose results enforce that the issues reported in this article are critical to harness the reported benefits of the MO-ITLBO.
Related Topics
Physical Sciences and Engineering Computer Science Artificial Intelligence
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