Multiobjective Optimization Problems With Complicated Pareto Sets, MOEA/D and NSGA-II

By Hui Li, Qingfu Zhang. IEEE Transactions on Evolutionary Computation, 2009

2,363 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/cd01342ef1459ba80aec884a5235407473fe2e27

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Citations in the corpus

Bat algorithm for multi-objective optimisation (2011, positive): “LZ4 function (Li and Zhang, 2009; Zhang and Li, 2007)”
jMetal: A Java framework for multi-objective optimization (2011, background): “A rich set of test problems including: – Problem families: Zitzler–Deb–Thiele (ZDT) [26], Deb– Thiele–Laumanns–Zitzler (DTLZ) [27], Walking-Fish-Group (WFG) test problems [28]), CEC2009 (unconstrained problems) [29], and the Li-Zhang benchmark [17].”
A Survey of Multi-Objective Optimization in Wireless Sensor Networks: Metrics, Algorithms, and Open Problems (2016, background): “MOEAs aim for finding a set of representative Pareto-optimal solutions in a single run [14], [19], [20].”
Using the Averaged Hausdorff Distance as a Performance Measure in Evolutionary Multiobjective Optimization (2012, methodology): “UF1 [30] f1(x) = x1 + 2 J1 ∑ j∈J1 |xj − sin(6πx1 + jπ/n)|2 f2(x) = 1 − √x1 + 2 J2 ∑ j∈J1 |xj − sin(6πx1 + jπ/n)|2 where J1 = {j|j is odd and 2 ≤ j ≤ n}, J2 = {j|j is even and 2 ≤ j ≤ n} x1 ∈ [0, 1] xi ∈ [−1, 1], i = 2, .”
A New Dominance Relation-Based Evolutionary Algorithm for Many-Objective Optimization (2016, methodology): “MOEA based on decomposition (MOEA/D) [33], [34] is the most typical implementation of this class.”
A Survey of Decomposition Methods for Multi-objective Optimization (2014, methodology): “In multi-objective decomposition the first implementation found is from Li and Zhang [27], an evolution of the first MOEA/D in Zhang and Li [14], called MOEA/D-DE.”
Evolutionary Compression of Deep Neural Networks for Biomedical Image Segmentation (2020, background): “Meanwhile, other ranking strategies [55] can be easily adopted into ECDNN according to practical requirements.”
An improved epsilon constraint-handling method in MOEA/D for CMOPs with large infeasible regions (2017, methodology): “The second type is decomposition-based approaches, and typical examples include MOEA/D (Zhang and Li (2007)), MOEA/D-DE (Li and Zhang (2009)), EAG-MOEA/D (Cai et al (2015)), MOEA/D-M2M (Liu et al (2014)), MOEA/D-SAS (Cai et al (2016)) and so on.”
Test Problems for Large-Scale Multiobjective and Many-Objective Optimization (2017, methodology): “Okabe et al. [27] proposed some design principles for constructing test problems with an arbitrarily complex PS, which were generalized in [28].”
A Strength Pareto Evolutionary Algorithm Based on Reference Direction for Multiobjective and Many-Objective Optimization (2017, background): “This way, MOEA/D is capable of solving different types of optimization problems with varying degrees of success [17], [24], [25], [33], [48].”
A Multiobjective Evolutionary Algorithm Using Gaussian Process-Based Inverse Modeling (2015, methodology): “Best PS and PF obtained using IM-MOEA among 20 single runs on (a) and (c) 10-D and (b) and (d) 30-D F3 introduced in [64], respectively.”
A Coevolutionary Framework for Constrained Multiobjective Optimization Problems (2021, background): “3) Genetic Operators: NSGA-II, C-TAEA, and CCMO adopt the simulated binary crossover [40] and the polynomial mutation [41] to generate offsprings, while PPS and ToP adopt the differential evolution [47] and the polynomial mutation to generate offsprings.”
Preference-Inspired Coevolutionary Algorithms for Many-Objective Optimization (2013, background): “replacement neighborhood size nr except that, in [30], the authors point out that T should be much smaller than the population size and nr should be much smaller than T .”
Evolutionary Constrained Multiobjective Optimization: Test Suite Construction and Performance Comparisons (2019, neutral): “Yang et al. [50] improved the -constrained method and investigated its performance in MOEA/D-DE.”