A review of population-based metaheuristics for large-scale black-box global optimization: Part B

Mohammad Nabi Omidvar1; Xiaodong Li2; Xin Yao3

2021

10.1109/TEVC.2021.3130835

IEEE Transactions on Evolutionary Computation   影响因子和分区

1941-0026

1941-0026

This article is the second part of a two-part survey series on large-scale global optimization. The first part covered two major algorithmic approaches to large-scale optimization, namely, decomposition methods and hybridization methods, such as memetic algorithms and local search. In this part, we focus on sampling and variation operators, approximation and surrogate modeling, initialization methods, and parallelization. We also cover a range of problem areas in relation to large-scale global optimization, such as multiobjective optimization, constraint handling, overlapping components, the component imbalance issue and benchmarks, and applications. The article also includes a discussion on pitfalls and challenges of the current research and identifies several potential areas of future research.

large-scale global optimization black-box optimization metaheuristics evolutionary optimization.

SCI ; EI

英语

其他

Australian Research Council (ARC)["DP180101170","DP190101271"] ; Shenzhen Science and Technology Program[KQTD2016112514355531] ; Program for Guangdong Introducing Innovative and Entrepreneurial Teams[2017ZT07X386] ; Program for University Key Laboratory of Guangdong Province[2017KSYS008]

Computer Science

Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods

WOS:000862385200006

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC

20214911284935

Approximation algorithms ; Benchmarking ; Constraint handling ; Global optimization ; Maintenance ; Multiobjective optimization ; Particle swarm optimization (PSO) ; Population statistics

Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory:721.1 ; Computer Software, Data Handling and Applications:723 ; Computer Programming:723.1 ; Maintenance:913.5 ; Mathematics:921 ; Optimization Techniques:921.5

COMPUTER SCIENCE

人工提交

1.University of Leeds
2.RMIT University
3.Department of Computer Science and Engineering, Southern University of Science and Technology

Mohammad Nabi Omidvar,Xiaodong Li,Xin Yao. A review of population-based metaheuristics for large-scale black-box global optimization: Part B[J]. IEEE Transactions on Evolutionary Computation,2021,PP(99):1-1.

Mohammad Nabi Omidvar,Xiaodong Li,&Xin Yao.(2021).A review of population-based metaheuristics for large-scale black-box global optimization: Part B.IEEE Transactions on Evolutionary Computation,PP(99),1-1.

Mohammad Nabi Omidvar,et al."A review of population-based metaheuristics for large-scale black-box global optimization: Part B".IEEE Transactions on Evolutionary Computation PP.99(2021):1-1.