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Soft Computing

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19.08.2023 | Optimization

A resource allocation-based multi-objective evolutionary algorithm for large-scale multi-objective optimization

verfasst von: Wanting Yang, Jianchang Liu, Wei Zhang, Xinnan Zhang

Erschienen in: Soft Computing | Ausgabe 23/2023

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Abstract

In large-scale multi-objective optimization problems (LSMOPs), multiple conflicting objectives and hundreds even thousands of decision variables are contained. Therefore, it is a great challenge to address LSMOPs due to the curse of dimensionality. To tackle LSMOPs, this paper proposes a resource allocation-based multi-objective optimization evolutionary algorithm. In the proposed algorithm, decision variables are firstly divided into convergence-related variables and diversity-related variables by the proposed layer thickness-based variable classification (LTVC) method. Then, a resource allocation-based convergence optimization strategy is introduced for the convergence-related variables, which can allocate more computational resource to the sub-component with the best contribution. For the diversity-related variables, diversity optimization technique is adopted. Finally, the experimental results verify that the proposed algorithm has a competitive performance compared with some state-of-the-art algorithms.

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Agrawal N, Kumar A, Bajaj V (2018) Design of digital iir filter with low quantization error using hybrid optimization technique. Soft Comput 22:2953–2971

Agrawal N, Kumar A, Bajaj V (2019) A new method for designing of stable digital iir filter using hybrid method. Circuits Syst Signal Process 38:2187–2226MathSciNet

Agrawal N, Kumar A, Bajaj V, Singh GK (2019) Design of bandpass and bandstop infinite impulse response filters using fractional derivative. IEEE Trans Industr Electron 66(2):1285–1295

Agrawal N, Kumar A, Bajaj V, Singh G (2021) Design of digital iir filter: a research survey. Appl Acoust 172:107669

Antonio LM, Coello CAC (2013) Use of cooperative coevolution for solving large scale multiobjective optimization problems. In: 2013 IEEE congress on evolutionary computation (CEC), pp 2758–2765

Beume N, Naujoks B, Emmerich M (2007) Sms-emoa: multiobjective selection based on dominated hypervolume. Eur J Oper Res 181(3):1653–1669MATH

Bosman P, Thierens D (2003) The balance between proximity and diversity in multiobjective evolutionary algorithms. IEEE Trans Evol Comput 7(2):174–188

Cao B, Zhao J, Lv Z, Liu X (2017) A distributed parallel cooperative coevolutionary multiobjective evolutionary algorithm for large-scale optimization. IEEE Trans Industr Inf 13(4):2030–2038

Chen H, Cheng R, Wen J, Li H, Weng J (2020) Solving large-scale many-objective optimization problems by covariance matrix adaptation evolution strategy with scalable small subpopulations. Inf Sci 509:457–469MathSciNetMATH

Cheng R, Jin Y, Olhofer M, Sendhoff B (2016) A reference vector guided evolutionary algorithm for many-objective optimization. IEEE Trans Evol Comput 20(5):773–791

Cheng S, Zhan H, Yao H, Fan H, Liu Y (2021) Large-scale many-objective particle swarm optimizer with fast convergence based on alpha-stable mutation and logistic function. Appl Soft Comput 99:106947

Chen W, Weise T, Yang Z, Tang K (2010) Large-scale global optimization using cooperative coevolution with variable interaction learning. In: Schaefer R, Cotta C, Kołodziej J, Rudolph G (eds) Parallel problem solving from nature. PPSN XI, Springer, Berlin Heidelberg, Berlin, Heidelberg, pp 300–309

Corless RM, Fillion N (2013) A graduate introduction to numerical methods. Springer, Berlin. https://doi.org/10.1007/978-1-4614-8453-0CrossRefMATH

Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: Nsga-ii. IEEE Trans Evol Comput 6(2):182–197

Deb K, Mohan M, Mishra S (2005) Evaluating the epsilon-domination based multi-objective evolutionary algorithm for a quick computation of pareto-optimal solutions. Evol Comput 13(4):501–525

Deb K, Thiele L, Laumanns M, Zitzler E (2005) Scalable test problems for evolutionary multiobjective optimization, pp 105–145

Dwivedi AK, Ghosh S, Londhe ND (2018) Review and analysis of evolutionary optimization-based techniques for fir filter design. Circuits Syst Signal Process 37:4409–4430

He Z, Yen GG (2017) Many-objective evolutionary algorithms based on coordinated selection strategy. IEEE Trans Evol Comput 21(2):220–233

He C, Li L, Tian Y, Zhang X, Cheng R, Jin Y, Yao X (2019) Accelerating large-scale multiobjective optimization via problem reformulation. IEEE Trans Evol Comput 23(6):949–961

He C, Cheng R, Yazdani D (2022) Adaptive offspring generation for evolutionary large-scale multiobjective optimization. IEEE Trans Syst Man Cybern Syst 52(2):786–798

Huband S, Hingston P, Barone L, While RL (2006) A review of multiobjective test problems and a scalable test problem toolkit. IEEE Trans Evol Comput 10:477–506MATH

Kumar A, Agrawal N, Sharma I (2020) Design of finite impulse response filter with controlled ripple using cuckoo search algorithm. In: Chaudhuri BB, Nakagawa M, Khanna P, Kumar S (eds) Proceedings of 3rd international conference on computer vision and image processing, Springer Singapore, Singapore, pp 471–482

Li H, Zhang Q (2009) Multiobjective optimization problems with complicated pareto sets, moea/d and nsga-ii. IEEE Trans Evol Comput 13(2):284–302

Li Y, Li L, Lin Q, Wong KC, Ming Z, Coello Coello CA (2022) A self-organizing weighted optimization based framework for large-scale multi-objective optimization. Swarm Evol Comput 72:101084

Liu Y, Gong D, Sun J, Jin Y (2017) A many-objective evolutionary algorithm using a one-by-one selection strategy. IEEE Trans Cybern 47(9):2689–2702

Liu Y, Liu J, Li T, Li Q (2020) An R2 indicator and weight vector-based evolutionary algorithm for multi-objective optimization. Soft Comput 24:5079–5100MATH

Liu Y, Liu J, Jin Y (2022) Surrogate-assisted multipopulation particle swarm optimizer for high-dimensional expensive optimization. IEEE Trans Syst Man Cybernet Syst 52(7):4671–4684

Liu J, Liu Y, Jin Y, Li F (2021) A decision variable assortment-based evolutionary algorithm for dominance robust multiobjective optimization. In: IEEE transactions on systems, man, and cybernetics: systems, pp 1–16

Ma X, Liu F, Qi Y, Wang X, Li L, Jiao L, Yin M, Gong M (2016) A multiobjective evolutionary algorithm based on decision variable analyses for multiobjective optimization problems with large-scale variables. IEEE Trans Evol Comput 20(2):275–298

Madani A, Engelbrecht A, Ombuki-Berman B (2023) Cooperative coevolutionary multi-guide particle swarm optimization algorithm for large-scale multi-objective optimization problems. Swarm Evol Comput 78:101262

Mahdavi S, Shiri ME, Rahnamayan S (2015) Metaheuristics in large-scale global continues optimization: a survey. Inf Sci 295:407–428MathSciNet

Miguel Antonio L, Coello Coello CA (2016) Decomposition-based approach for solving large scale multi-objective problems. In: Handl J, Hart E, Lewis PR, López-Ibáñez M, Ochoa G, Paechter B (eds) Parallel problem solving from nature - PPSN XIV. Springer International Publishing, Cham, pp 525–534

Omidvar MN, Kazimipour B, Li X, Yao X (2016) Cbcc3-a contribution-based cooperative co-evolutionary algorithm with improved exploration/exploitation balance. In: 2016 IEEE congress on evolutionary computation (CEC), pp 3541–3548

Omidvar MN, Li X, Yang Z, Yao X (2010) Cooperative co-evolution for large scale optimization through more frequent random grouping. In: IEEE congress on evolutionary computation (CEC), pp 1–8

Omidvar MN, Li X, Yao X (2011) Smart use of computational resources based on contribution for cooperative co-evolutionary algorithms. In: Proceedings of the 13th annual conference on genetic and evolutionary computation, pp 1115–1122

Omidvar MN, Li X, Mei Y, Yao X (2014) Cooperative co-evolution with differential grouping for large scale optimization. IEEE Trans Evol Comput 18(3):378–393

Omidvar MN, Yang M, Mei Y, Li X, Yao X (2017) Dg2: a faster and more accurate differential grouping for large-scale black-box optimization. IEEE Trans Evol Comput 21(6):929–942

Qin S, Sun C, Jin Y, Tan Y, Fieldsend J (2021) Large-scale evolutionary multiobjective optimization assisted by directed sampling. IEEE Trans Evol Comput 25(4):724–738

Saha SK, Kar R, Mandal D, Ghoshal SP (2013) Bacteria foraging optimisation algorithm for optimal fir filter design. Int J Bio-Inspired Comput 5:52–66

Saha SK, Kar R, Mandal D, Ghoshal SP (2013) Design and simulation of fir band pass and band stop filters using gravitational search algorithm. Memetic Comput 5:311–321

Song A, Yang Q, Chen WN, Zhang J (2016) A random-based dynamic grouping strategy for large scale multi-objective optimization. In: 2016 IEEE congress on evolutionary computation (CEC), pp 468–475

Tian Y, Cheng R, Zhang X, Jin Y (2017) Platemo: a matlab platform for evolutionary multi-objective optimization [educational forum]. IEEE Comput Intell Mag 12(4):73–87

Tian Y, Zheng X, Zhang X, Jin Y (2020) Efficient large-scale multiobjective optimization based on a competitive swarm optimizer. IEEE Trans Cybern 50(8):3696–3708

Tian Y, Zhang X, Wang C, Jin Y (2020) An evolutionary algorithm for large-scale sparse multiobjective optimization problems. IEEE Trans Evol Comput 24(2):380–393

Tian Y, Zhang X, Cheng R, Jin Y (2016) A multi-objective evolutionary algorithm based on an enhanced inverted generational distance metric. In: 2016 IEEE congress on evolutionary computation (CEC), pp 5222–5229

Van Aelst S, (Steven) Wang X, Zamar RH, Zhu R (2006) Linear grouping using orthogonal regression. Comput Stat Data Anal 50(5):1287–1312

Wang H, Jiao L, Shang R, He S, Liu F (2015) A memetic optimization strategy based on dimension reduction in decision space. Evol Comput 23(1):69–100

Yang M, Omidvar MN, Li C, Li X, Cai Z, Kazimipour B, Yao X (2017) Efficient resource allocation in cooperative co-evolution for large-scale global optimization. IEEE Trans Evol Comput 21(4):493–505

Yang Y, Liu J, Tan S, Liu Y (2021) A multi-objective differential evolution algorithm based on domination and constraint-handling switching. Inf Sci 579:796–813MathSciNet

Yi JH, Xing LN, Wang GG, Dong J, Vasilakos AV, Alavi AH, Wang L (2020) Behavior of crossover operators in nsga-iii for large-scale optimization problems. Inf Sci 509:470–487MathSciNet

Zhang Q, Li H (2007) Moea/d: a multiobjective evolutionary algorithm based on decomposition. IEEE Trans Evol Comput 11(6):712–731

Zhang X, Tian Y, Cheng R, Jin Y (2018) A decision variable clustering-based evolutionary algorithm for large-scale many-objective optimization. IEEE Trans Evol Comput 22(1):97–112

Zhang X, Zheng X, Cheng R, Qiu J, Jin Y (2018) A competitive mechanism based multi-objective particle swarm optimizer with fast convergence. Inf Sci 427:63–76MathSciNet

Zhang Y, Wang GG, Li K, Yeh WC, Jian M, Dong J (2020) Enhancing moea/d with information feedback models for large-scale many-objective optimization. Inf Sci 522:1–16MathSciNetMATH

Zille H, Ishibuchi H, Mostaghim S, Nojima Y (2018) A framework for large-scale multiobjective optimization based on problem transformation. IEEE Trans Evol Comput 22(2):260–275

Zitzler E, Thiele L (1999) Multiobjective evolutionary algorithms: a comparative case study and the strength pareto approach. IEEE Trans Evol Comput 3(4):257–271

Zitzler E, Laumanns M, Thiele L (2001) Spea2: improving the strength pareto evolutionary algorithm. Technical Report Gloriastrasse

Titel: A resource allocation-based multi-objective evolutionary algorithm for large-scale multi-objective optimization
verfasst von: Wanting Yang
Jianchang Liu
Wei Zhang
Xinnan Zhang
Publikationsdatum: 19.08.2023
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 23/2023
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-023-09061-4

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