Multi-objective Pelican Optimization Algorithm for Engineering Design Problems

被引:3
作者
Naidu, Y. Ramu [1 ]
机构
[1] Natl Inst Technol Andhra Pradesh, Sch Sci, Tadepalligudem, Andhra Pradesh, India
来源
DISTRIBUTED COMPUTING AND INTELLIGENT TECHNOLOGY, ICDCIT 2023 | 2023年 / 13776卷
关键词
Pelican optimization algorithm; Multi-objective problems; Engineering design problems;
D O I
10.1007/978-3-031-24848-1_28
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This work presents an efficient multi-objective version of the Pelican Optimization Algorithm (POA) which is recently proposed in the family of meta-heuristic algorithms. It is called a multi-objective Pelican Optimization Algorithm (MOPOA). From the literature, it is observed that the POA performed well on a set of unconstrained classical optimization problems as well as some engineering design problems. To extend its applicability to multi-objective engineering design models, the MOPOA has been proposed and applied for two engineering design models, four bar truss and speed reducer problems. The obtained results are compared with the literature and they proved that the MOPOA is an efficient and robust optimizer.
引用
收藏
页码:362 / 368
页数:7
相关论文
共 50 条
  • [41] Self-adaptive Equilibrium Optimizer for solving global, combinatorial, engineering, and Multi-Objective problems
    Houssein, Essam H.
    Celik, Emre
    Mahdy, Mohamed A.
    Ghoniem, Rania M.
    EXPERT SYSTEMS WITH APPLICATIONS, 2022, 195
  • [42] EABOA: Enhanced adaptive butterfly optimization algorithm for numerical optimization and engineering design problems
    He, Kai
    Zhang, Yong
    Wang, Yu-Kun
    Zhou, Rong-He
    Zhang, Hong-Zhi
    ALEXANDRIA ENGINEERING JOURNAL, 2024, 87 : 543 - 573
  • [43] A solution to multi Objective Stochastic Optimal Power Flow problem using mutualism and elite strategy based Pelican Optimization Algorithm
    Dora, Bimal Kumar
    Bhat, Sunil
    Halder, Sudip
    Srivastava, Ishan
    APPLIED SOFT COMPUTING, 2024, 158
  • [44] SUB-POPULATION GENETIC ALGORITHM II FOR MULTI-OBJECTIVE PARALLEL MACHINE SCHEDULING PROBLEMS
    Huang, Wei-Hsiu
    Chang, Pei-Chann
    Kuo, Chun-Yin
    Hsu, Lin
    Chen, Meng-Huei
    THIRD INTERNATIONAL CONFERENCE ON COMPUTER ENGINEERING AND TECHNOLOGY (ICCET 2011), 2011, : 197 - 202
  • [45] A Novel Pareto Archive Evolution Algorithm with Adaptive Grid Strategy for Multi-objective Optimization Problem
    Zhao, Fuqing
    He, Xuan
    Zhang, Yi
    Ma, Weimin
    Zhang, Chuck
    PROCEEDINGS OF THE 2019 IEEE 23RD INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED COOPERATIVE WORK IN DESIGN (CSCWD), 2019, : 301 - 306
  • [46] Learning automata-based butterfly optimization algorithm for engineering design problems
    Arora, Sankalap
    Anand, Priyanka
    INTERNATIONAL JOURNAL OF COMPUTATIONAL MATERIALS SCIENCE AND ENGINEERING, 2018, 7 (04)
  • [47] Growing Particle Swarm Optimizers for Multi-Objective Problems in Design of DC-AC Inverters
    Ono, Katsuma
    Jin'no, Kenya
    Saito, Toshimichi
    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, 2011, E94A (01) : 430 - 433
  • [48] Multi-strategy Improved Pelican Optimization Algorithm for Mobile Robot Path Planning
    Li, Chun Qing
    Jiang, Zheng Feng
    Huang, Yong Ping
    INFORMATION TECHNOLOGY AND CONTROL, 2024, 53 (02): : 372 - 389
  • [49] An Improved Rider Optimization Algorithm for Solving Engineering Optimization Problems
    Wang, Guohu
    Yuan, Yongliang
    Guo, Wenwen
    IEEE ACCESS, 2019, 7 : 80570 - 80576
  • [50] Deep Statistical Comparison for Multi-Objective Stochastic Optimization Algorithms
    Eftimov, Tome
    Korosec, Peter
    SWARM AND EVOLUTIONARY COMPUTATION, 2021, 61