Benchmark testing

Lamarckian Platform: Pushing the Boundaries of Evolutionary Reinforcement Learning Towards Asynchronous Commercial Games
Despite the emerging progress of integrating evolutionary computation into reinforcement learning, the absence of a high-performance …
Hui Bai, Ruimin Shen, Yue Lin, Botian Xu, Ran Cheng
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Neural Architecture Search as Multiobjective Optimization Benchmarks: Problem Formulation and Performance Assessment
The ongoing advancements in network architecture design have led to remarkable achievements in deep learning across various challenging …
Zhichao Lu, Ran Cheng, Yaochu Jin, Kay Chen Tan, Kalyanmoy Deb
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A Survey of Evolutionary Continuous Dynamic Optimization Over Two Decades—Part A
Many real-world optimization problems are dynamic. The field of dynamic optimization deals with such problems where the search space …
Danial Yazdani, Ran Cheng, Donya Yazdani, Jürgen Branke, Yaochu Jin, Xin Yao
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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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A Survey of Evolutionary Continuous Dynamic Optimization Over Two Decades—Part B
This article presents the second Part of a two-Part survey that reviews evolutionary dynamic optimization (EDO) for single-objective …
Danial Yazdani, Ran Cheng, Donya Yazdani, Jürgen Branke, Yaochu Jin, Xin Yao
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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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Evolutionary Large-Scale Multiobjective Optimization for Ratio Error Estimation of Voltage Transformers
Ratio error (RE) estimation of the voltage transformers (VTs) plays an important role in modern power delivery systems. Existing RE …
Cheng He, Ran Cheng, Chuanji Zhang, Ye Tian, Qin Chen, Xin Yao
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Diversity Assessment of Multi-Objective Evolutionary Algorithms: Performance Metric and Benchmark Problems [Research Frontier]
Diversity preservation plays an important role in the design of multi-objective evolutionary algorithms, but the diversity performance …
Ye Tian, Ran Cheng, Xingyi Zhang, Miqing Li, Yaochu Jin
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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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Sampling Reference Points on the Pareto Fronts of Benchmark Multi-Objective Optimization Problems
The effectiveness of evolutionary algorithms have been verified on multi-objective optimization, and a large number of multi-objective …
Ye Tian, Xiaoshu Xiang, Xingyi Zhang, Ran Cheng, Yaochu Jin
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