Linear programming

Reference Vector-Assisted Adaptive Model Management for Surrogate-Assisted Many-Objective Optimization
Acquisition functions for surrogate-assisted many-objective optimization require a delicate balance between convergence and diversity. …
Qiqi Liu, Ran Cheng, Yaochu Jin, Martin Heiderich, Tobias Rodemann
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Large-scale Multiobjective Optimization via Problem Decomposition and Reformulation
Large-scale multiobjective optimization problems (LSMOPs) are challenging for existing approaches due to the complexity of objective …
Lianghao Li, Cheng He, Ran Cheng, Linqiang Pan
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Benchmarking Continuous Dynamic Optimization: Survey and Generalized Test Suite
Dynamic changes are an important and inescapable aspect of many real-world optimization problems. Designing algorithms to find and …
Danial Yazdani, Mohammad Nabi Omidvar, Ran Cheng, Jürgen Branke, Trung Thanh Nguyen, Xin Yao
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A Hybrid Surrogate-Assisted Evolutionary Algorithm for Computationally Expensive Many-Objective Optimization
Many real-world optimization problems are challenging because the evaluation of solutions is computationally expensive. As a result, …
Kanzhen Wan, Cheng He, Auraham Camacho, Ke Shang, Ran Cheng, Hisao Ishibuchi
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Solving Incremental Optimization Problems via Cooperative Coevolution
Engineering designs can involve multiple stages, where at each stage, the design models are incrementally modified and optimized. In …
Ran Cheng, Mohammad Nabi Omidvar, Amir H. Gandomi, Bernhard Sendhoff, Stefan Menzel, Xin Yao
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Evolutionary Multiobjective Optimization-Based Multimodal Optimization: Fitness Landscape Approximation and Peak Detection
Recently, by taking advantage of evolutionary multiobjective optimization techniques in diversity preservation, the means of …
Ran Cheng, Miqing Li, Ke Li, Xin Yao
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Test Problems for Large-Scale Multiobjective and Many-Objective Optimization
The interests in multiobjective and many-objective optimization have been rapidly increasing in the evolutionary computation community. …
Ran Cheng, Yaochu Jin, Markus Olhofer, Bernhard Sendhoff
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A Reference Vector Guided Evolutionary Algorithm for Many-Objective Optimization
In evolutionary multiobjective optimization, maintaining a good balance between convergence and diversity is particularly crucial to …
Ran Cheng, Yaochu Jin, Markus Olhofer, Bernhard Sendhoff
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