A note on multi-objective improved teaching-learning based optimization algorithm (MO-ITLBO)

被引:16
|
作者
Chinta, Sivadurgaprasad [1 ]
Kommadath, Remya [1 ]
Kotecha, Prakash [1 ]
机构
[1] Indian Inst Technol Guwahati, Dept Chem Engn, Gauhati 781039, Assam, India
关键词
Teaching-learning based optimization; Improved teachinglearning based optimization; Multi-objective optimization; Pareto dominance; Epsilon dominance; DESIGN; FLOW;
D O I
10.1016/j.ins.2016.08.061
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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. (C) 2016 Elsevier Inc. All rights reserved.
引用
收藏
页码:337 / 350
页数:14
相关论文
共 50 条
  • [1] A multi-objective improved teaching-learning based optimization algorithm (MO-ITLBO)
    Patel, Vivek K.
    Savsani, Vimal J.
    INFORMATION SCIENCES, 2016, 357 : 182 - 200
  • [2] Optimization of a plate-fin heat exchanger design through an improved multi-objective teaching-learning based optimization (MO-ITLBO) algorithm
    Patel, Vivek
    Savsani, Vimal
    CHEMICAL ENGINEERING RESEARCH & DESIGN, 2014, 92 (11): : 2371 - 2382
  • [3] Dynamic placement of virtual machines using an improved multi-objective teaching-learning based optimization algorithm in cloud
    Wang, Na
    Osmani, Amjad
    Mirzaei, Siamak
    TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES, 2022, 33 (09)
  • [4] Dynamic Resource Allocation Using an Adaptive Multi-Objective Teaching-Learning Based Optimization Algorithm in Cloud
    Moazeni, Ali
    Khorsand, Reihaneh
    Ramezanpour, Mohammadreza
    IEEE ACCESS, 2023, 11 : 23407 - 23419
  • [5] Multi-Objective Optimal Power Flow Using a Modified Weighted Teaching-Learning Based Optimization Algorithm
    Ermis, S.
    ELECTRIC POWER COMPONENTS AND SYSTEMS, 2023, 51 (20) : 2536 - 2556
  • [6] An Improved Multi-objective Optimization Algorithm Based on Reinforcement Learning
    Liu, Jun
    Zhou, Yi
    Qiu, Yimin
    Li, Zhongfeng
    ADVANCES IN SWARM INTELLIGENCE, ICSI 2022, PT I, 2022, : 501 - 513
  • [7] Three-objective optimization of boiler combustion process based on multi-objective teaching-learning based optimization algorithm and ameliorated extreme learning machine
    Ma, Yunpeng
    Wang, Heqi
    Zhang, Xinxin
    Hou, Likun
    Song, Jiancai
    MACHINE LEARNING WITH APPLICATIONS, 2021, 5
  • [8] Multi-objective optimization using teaching-learning-based optimization algorithm
    Zou, Feng
    Wang, Lei
    Hei, Xinhong
    Chen, Debao
    Wang, Bin
    ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2013, 26 (04) : 1291 - 1300
  • [9] An Improved Elitism Based Teaching-Learning Optimization Algorithm
    Bhadoria, Anjali
    Singh, Madhuraj
    Gupta, Manish
    2016 INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONICS, AND OPTIMIZATION TECHNIQUES (ICEEOT), 2016, : 3726 - 3730
  • [10] A Multi-Objective Feedback Teaching-Learning-Based Optimization Algorithm
    Qiu, Jie
    Xu, Kun
    Hu, Wenqian
    Ren, Ziwu
    2019 CHINESE AUTOMATION CONGRESS (CAC2019), 2019, : 867 - 872