On Algorithmic Descriptions and Software Implementations for Multi-objective Optimisation: A Comparative Study

被引:0
|
作者
Rostami S. [1 ,2 ]
Neri F. [3 ]
Gyaurski K. [2 ]
机构
[1] Data Science Lab, Polyra Limited, Bournemouth
[2] Department of Computing and Informatics, Bournemouth University, Bournemouth
[3] COL Laboratory, School of Computer Science, University of Nottingham, Nottingham
关键词
Evolutionary algorithms; Multi-objective optimisation; Optimisation software platforms;
D O I
10.1007/s42979-020-00265-1
中图分类号
学科分类号
摘要
Multi-objective optimisation is a prominent subfield of optimisation with high relevance in real-world problems, such as engineering design. Over the past 2 decades, a multitude of heuristic algorithms for multi-objective optimisation have been introduced and some of them have become extremely popular. Some of the most promising and versatile algorithms have been implemented in software platforms. This article experimentally investigates the process of interpreting and implementing algorithms by examining multiple popular implementations of three well-known algorithms for multi-objective optimisation. We observed that official and broadly employed software platforms interpreted and thus implemented the same heuristic search algorithm differently. These different interpretations affect the algorithmic structure as well as the software implementation. Numerical results show that these differences cause statistically significant differences in performance. © 2020, The Author(s).
引用
收藏
相关论文
共 50 条
  • [41] Multi-objective Optimisation with Multiple Preferred Regions
    Mahbub, Md. Shahriar
    Wagner, Markus
    Crema, Luigi
    ARTIFICIAL LIFE AND COMPUTATIONAL INTELLIGENCE, ACALCI 2017, 2017, 10142 : 241 - 253
  • [42] Multi-objective optimisation of composite aerospace structures
    Wang, K
    Kelly, D
    Dutton, S
    COMPOSITE STRUCTURES, 2002, 57 (1-4) : 141 - 148
  • [43] Scantling multi-objective optimisation of a LNG carrier
    Caprace, J. -D.
    Bair, F.
    Rigo, P.
    MARINE STRUCTURES, 2010, 23 (03) : 288 - 302
  • [44] Multi-objective optimisation of a floating LNG terminal
    Boulougouris, Evangelos K.
    Papanikolaou, Apostolos D.
    OCEAN ENGINEERING, 2008, 35 (8-9) : 787 - 811
  • [45] Multi-objective optimisation of sewer maintenance scheduling
    Draude, Sabrina
    Keedwell, Ed
    Kapelan, Zoran
    Hiscock, Rebecca
    JOURNAL OF HYDROINFORMATICS, 2022, 24 (03) : 574 - 589
  • [46] Evolutionary Multi-objective Optimisation in Neurotrajectory Prediction
    Galvan, Edgar
    Stapleton, Fergal
    APPLIED SOFT COMPUTING, 2023, 146
  • [47] MVMOO: Mixed variable multi-objective optimisation
    Jamie A. Manson
    Thomas W. Chamberlain
    Richard A. Bourne
    Journal of Global Optimization, 2021, 80 : 865 - 886
  • [48] Grid services for multi-objective design optimisation
    Goteng, G.
    Tiwari, A.
    Roy, R.
    CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY, 2010, 3 (04) : 249 - 261
  • [49] A New Multi-objective Model for Constrained Optimisation
    Xu, Tao
    He, Jun
    Shang, Changjing
    Ying, Weiqin
    ADVANCES IN COMPUTATIONAL INTELLIGENCE SYSTEMS, 2017, 513 : 71 - 85
  • [50] Multi-objective optimisation of restricted complexity controllers
    Cao, Y
    Yan, W
    EUROPEAN JOURNAL OF CONTROL, 2003, 9 (01) : 61 - 65