A Benchmark-Suite of real-World constrained multi-objective optimization problems and some baseline results

Generally, Synthetic Benchmark Problems (SBPs) are utilized to assess the performance of metaheuristics. However, these SBPs may include various unrealistic properties. As a consequence, performance assessment may lead to underestimation or overestimation. To address this issue, few benchmark suites...

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Vydané v:Swarm and evolutionary computation Ročník 67; s. 100961
Hlavní autori: Kumar, Abhishek, Wu, Guohua, Ali, Mostafa Z., Luo, Qizhang, Mallipeddi, Rammohan, Suganthan, Ponnuthurai Nagaratnam, Das, Swagatam
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier B.V 01.12.2021
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ISSN:2210-6502
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Abstract Generally, Synthetic Benchmark Problems (SBPs) are utilized to assess the performance of metaheuristics. However, these SBPs may include various unrealistic properties. As a consequence, performance assessment may lead to underestimation or overestimation. To address this issue, few benchmark suites containing real-world problems have been proposed for all kinds of metaheuristics except for Constrained Multi-objective Metaheuristics (CMOMs). To fill this gap, we develop a benchmark suite of Real-world Constrained Multi-objective Optimization Problems (RWCMOPs) for performance assessment of CMOMs. This benchmark suite includes 50 problems collected from various streams of research. We also present the baseline results of this benchmark suite by using state-of-the-art algorithms. Besides, for comparative analysis, a ranking scheme is also proposed.
AbstractList Generally, Synthetic Benchmark Problems (SBPs) are utilized to assess the performance of metaheuristics. However, these SBPs may include various unrealistic properties. As a consequence, performance assessment may lead to underestimation or overestimation. To address this issue, few benchmark suites containing real-world problems have been proposed for all kinds of metaheuristics except for Constrained Multi-objective Metaheuristics (CMOMs). To fill this gap, we develop a benchmark suite of Real-world Constrained Multi-objective Optimization Problems (RWCMOPs) for performance assessment of CMOMs. This benchmark suite includes 50 problems collected from various streams of research. We also present the baseline results of this benchmark suite by using state-of-the-art algorithms. Besides, for comparative analysis, a ranking scheme is also proposed.
ArticleNumber 100961
Author Wu, Guohua
Suganthan, Ponnuthurai Nagaratnam
Luo, Qizhang
Mallipeddi, Rammohan
Kumar, Abhishek
Ali, Mostafa Z.
Das, Swagatam
Author_xml – sequence: 1
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  surname: Kumar
  fullname: Kumar, Abhishek
  organization: Department of Artificial Intelligence, Kyungpook National University, Daegu 41566, Republic of Korea
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  givenname: Guohua
  surname: Wu
  fullname: Wu, Guohua
  organization: School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
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  givenname: Mostafa Z.
  surname: Ali
  fullname: Ali, Mostafa Z.
  organization: School of Computer Information Systems, Jordan University of Science & Technology, 22110, Jordan
– sequence: 4
  givenname: Qizhang
  surname: Luo
  fullname: Luo, Qizhang
  organization: School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China
– sequence: 5
  givenname: Rammohan
  orcidid: 0000-0001-9071-1145
  surname: Mallipeddi
  fullname: Mallipeddi, Rammohan
  email: mallipeddi.ram@gmail.com
  organization: Department of Artificial Intelligence, School of Electronics Engineering, Kyungpook National University, Daegu 41566, Republic of Korea
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  givenname: Ponnuthurai Nagaratnam
  surname: Suganthan
  fullname: Suganthan, Ponnuthurai Nagaratnam
  organization: School of Electrical Electronic Engineering, Nanyang Technological University, 639798, Singapore
– sequence: 7
  givenname: Swagatam
  surname: Das
  fullname: Das, Swagatam
  organization: Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India
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Multi-Objective constrained optimization
Benchmark-Suite
Ranking scheme
Metaheuristics
Performance assessment
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Snippet Generally, Synthetic Benchmark Problems (SBPs) are utilized to assess the performance of metaheuristics. However, these SBPs may include various unrealistic...
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StartPage 100961
SubjectTerms Benchmark-Suite
Metaheuristics
Multi-Objective constrained optimization
Performance assessment
Ranking scheme
Real-World problems
Title A Benchmark-Suite of real-World constrained multi-objective optimization problems and some baseline results
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