ε-constraint heat transfer search (ε-HTS) algorithm for solving multi-objective engineering design problems

被引:16
|
作者
Tawhid, Mohamed A. [1 ,2 ]
Savsani, Vimal [1 ,3 ]
机构
[1] Thompson Rivers Univ, Dept Math & Stat, Fac Sci, Kamloops, BC V2C 0C8, Canada
[2] Alexandria Univ, Dept Math & Comp Sci, Fac Sci, Moharam Bey 21511, Alexandria, Egypt
[3] Pandit Deendayal Petr Univ, Dept Mech Engn, Gandinagar, Gujarat, India
基金
加拿大自然科学与工程研究理事会;
关键词
Multiobjective optimization; Heat transfer search; Design optimization; Pareto front; MULTI OBJECTIVE OPTIMIZATION; EVOLUTIONARY ALGORITHMS; THERMODYNAMIC ANALYSIS; PARTICLE SWARM; PERFORMANCE; EFFICIENT; EMISSION; SYSTEM; FLOW;
D O I
10.1016/j.jcde.2017.06.003
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, an effective epsilon-constraint heat transfer search (e-HTS) algorithm for the multi-objective engineering design problems is presented. This algorithm is developed to solve multi-objective optimization problems by evaluating a set of single objective sub-problems. The effectiveness of the proposed algorithm is checked by implementing it on multi-objective benchmark problems that have various characteristics of Pareto front such as discrete, convex, and non-convex. This algorithm is also tested for several distinctive multi-objective engineering design problems, such as four bar truss problem, gear train problem, multi-plate disc brake design, speed reducer problem, welded beam design, and spring design problem. Moreover, the numerical experimentation shows that the proposed algorithm generates the solution to represent true Pareto front. (C) 2017 Society for Computational Design and Engineering. Publishing Services by Elsevier. This is an open access article under the CC BY-NC-ND license.
引用
收藏
页码:104 / 119
页数:16
相关论文
共 50 条
  • [21] A novel multi-objective optimization algorithm based on artificial algae for multi-objective engineering design problems
    Tawhid, Mohamed A.
    Savsani, Vimal
    APPLIED INTELLIGENCE, 2018, 48 (10) : 3762 - 3781
  • [22] A symbiotic organisms search algorithm-based design optimization of constrained multi-objective engineering design problems
    Ustun, Deniz
    Carbas, Serdar
    Toktas, Abdurrahim
    ENGINEERING COMPUTATIONS, 2021, 38 (02) : 632 - 658
  • [23] A Niching Multi-objective Harmony Search Algorithm for Multimodal Multi-objective Problems
    Qu, B. Y.
    Li, G. S.
    Guo, Q. Q.
    Yan, L.
    Chai, X. Z.
    Guo, Z. Q.
    2019 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), 2019, : 1267 - 1274
  • [24] Altruistic population algorithm: A metaheuristic search algorithm for solving multimodal multi-objective optimization problems
    Ouyang, Haibin
    Chen, Jianhong
    Li, Steven
    Xiang, Jianhua
    Zhan, Zhi-Hui
    MATHEMATICS AND COMPUTERS IN SIMULATION, 2023, 210 : 296 - 319
  • [25] MOMPA: Multi-objective marine predator algorithm for solving multi-objective optimization problems
    Jangir, Pradeep
    Buch, Hitarth
    Mirjalili, Seyedali
    Manoharan, Premkumar
    EVOLUTIONARY INTELLIGENCE, 2023, 16 (01) : 169 - 195
  • [26] A new multi-objective evolutionary algorithm for solving high complex multi-objective problems
    Li, Kangshun
    Yue, Xuezhi
    Kang, Lishan
    Chen, Zhangxin
    GECCO 2006: GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE, VOL 1 AND 2, 2006, : 745 - +
  • [27] A Multi-Objective Carnivorous Plant Algorithm for Solving Constrained Multi-Objective Optimization Problems
    Yang, Yufei
    Zhang, Changsheng
    BIOMIMETICS, 2023, 8 (02)
  • [28] MOMPA: Multi-objective marine predator algorithm for solving multi-objective optimization problems
    Pradeep Jangir
    Hitarth Buch
    Seyedali Mirjalili
    Premkumar Manoharan
    Evolutionary Intelligence, 2023, 16 : 169 - 195
  • [29] A Decomposition based Multi-Objective Heat Transfer Search algorithm for structure optimization
    Kumar, Sumit
    Jangir, Pradeep
    Tejani, Ghanshyam G.
    Premkumar, Manoharan
    KNOWLEDGE-BASED SYSTEMS, 2022, 253
  • [30] Multi-objective sine-cosine algorithm (MO-SCA) for multi-objective engineering design problems
    Mohamed A. Tawhid
    Vimal Savsani
    Neural Computing and Applications, 2019, 31 : 915 - 929