A benchmark test suite for evolutionary many-objective optimization

Complex & Intelligent Systems - Tập 3 Số 1 - Trang 67-81 - 2017
Ran Cheng1, Miqing Li1, Ye Tian2, Xingyi Zhang2, Shengxiang Yang3, Yaochu Jin4, Xin Yao5
1CERCIA, School of Computer Science, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
2School of Computer Science and Technology, Anhui University, Hefei 230039, China
3School of Computer Science and Informatics, De Monfort University, Leicester, LE1 9BH, UK
4Department of Computer Science, University of Surrey, Guildford, Surrey, GU2 7XH, UK
5Department of Computer Science and Engineering, Southern University of Science and Technology, 518055, Shenzhen, China

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Tài liệu tham khảo

Li B, Li J, Tang K, Yao X (2015) Many-objective evolutionary algorithms: a survey. ACM Comput Surv 48(1):13

Yang S, Li M, Liu X, Zheng J (2013) A grid-based evolutionary algorithm for many-objective optimization. IEEE Trans Evol Comput 17(5):721–736

Zhang X, Tian Y, Jin Y (2015) A knee point driven evolutionary algorithm for many-objective optimization. IEEE Trans Evol Comput 19(6):761–776

Wang H, Jiao L, Yao X (2015) Two_arch2: an improved two-archive algorithm for many-objective optimization. IEEE Trans Evol Comput 19(4):524–541

Deb K, Jain H (2014) An evolutionary many-objective optimization algorithm using reference-point-based nondominated sorting approach, part I: solving problems with box constraints. IEEE Trans Evol Comput 18(4):577–601

Li K, Zhang Q, Kwong S (2015) An evolutionary many-objective optimization algorithm based on dominance and decomposition. IEEE Trans Evol Comput 19(5):694–716

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

Bader J, Zitzler E (2011) HypE: an algorithm for fast hypervolume-based many-objective optimization. Evol Comput 19(1):45–76

Deb K, Thiele L, Laumanns M, Zitzler E (2005) Scalable test problems for evolutionary multiobjective optimization. In: Abraham A, Jain L, Goldberg R (eds) Evolutionary multiobjective optimization. Theoretical advances and applications, Springer, Berlin, pp 105–145

Huband S, Hingston P, Barone L, While L (2006) A review of multiobjective test problems and a scalable test problem toolkit. IEEE Trans Evol Comput 10(5):477–506

Köppen M, Yoshida K (2007) Substitute distance assignments in NSGA-II for handling many-objective optimization problems. In: Evolutionary multi-criterion optimization (EMO), pp 727–741

Ishibuchi H, Hitotsuyanagi Y, Tsukamoto N, Nojima Y (2010) Many-objective test problems to visually examine the behavior of multiobjective evolution in a decision space. In: International Conference on Parallel Problem Solving from Nature (PPSN), pp 91–100

Saxena D, Zhang Q, Duro J, Tiwari A (2011) Framework for many-objectivet test problems with both simple and complicated Pareto-set shapes. In: Evolutionary multi-criterion optimization (EMO), pp 197–211

Li M, Yang S, Liu X (2014) A test problem for visual investigation of high-dimensional multi-objective search. In: IEEE Congress on Evolutionary Computation (CEC), pp 2140–2147

Cheung Y-M, Gu F, Liu H-L (2016) Objective extraction for many-objective optimization problems: Algorithm and test problems. IEEE Trans Evol Comput 20(5):755–772

Cheng R, Jin Y, Olhofer M, Sendhoff B (2016) Test problems for large-scale multiobjective and many-objective optimization. IEEE Trans Cybern (in press)

Masuda H, Nojima Y, Ishibuchi H (2016) Common properties of scalable multiobjective problems and a new framework of test problems. In: IEEE Congress on Evolutionary Computation (CEC). IEEE, pp 3011–3018

Cheng R, Jin Y, Narukawa K (2015) Adaptive reference vector generation for inverse model based evolutionary multiobjective optimization with degenerate and disconnected pareto fronts. In: Proceedings of the International Conference on Evolutionary Multi-Criterion Optimization. Springer, New York, pp 127–140

Brockhoff D, Zitzler E (2009) Objective reduction in evolutionary multiobjective optimization: theory and applications. Evol Comput 17(2):135–166

Li M, Yang S, Liu X (2016) Pareto or non-Pareto: Bi-criterion evolution in multi-objective optimization. IEEE Trans Evol Comput 20(5):645–665

Saxena D, Duro J, Tiwari A, Deb K, Zhang Q (2013) Objective reduction in many-objective optimization: linear and nonlinear algorithms. IEEE Trans Evol Comput 17(1):77–99

Ishibuchi H, Masuda H, Nojima Y (2016) Pareto fronts of many-objective degenerate test problems. IEEE Trans Evol Comput 20(5):807–813

Jain H, Deb K (2014) An evolutionary many-objective optimization algorithm using reference-point based nondominated sorting approach, part II: handling constraints and extending to an adaptive approach. IEEE Trans Evol Comput 18(4):602–622

Deb K, Saxena DK (2006) Searching for Pareto-optimal solutions through dimensionality reduction for certain large-dimensional multi-objective optimization problems. In: IEEE Congress on Evolutionary Computation (CEC), pp 3353–3360

Li M, Grosan C, Yang S, Liu X, Yao X (2017) “Multi-line distance minimization: A visualized many-objective test problem suite. IEEE Trans Evol Comput (in press)

Tian Y, Cheng R, Zhang X, Jin Y (2016) Platemo: a matlab platform for evolutionary multi-objective optimization. IEEE Comput Intell Mag (under review)