An Open Framework for Constructing Continuous Optimization Problems

作者：Li, Changhe^*; Trung Thanh Nguyen; Zeng, Sanyou; Yang, Ming; Wu, Min

来源：IEEE Transactions on Cybernetics, 2019, 49(6): 2316-2330.

DOI：10.1109/TCYB.2018.2825343

• Continuous optimization
• dynamic optimization
• free peaks (FPs)
• global optimization
• multimodal optimization
• multiobjective optimization

Many artificial benchmark problems have been proposed for different kinds of continuous optimization, e.g., global optimization, multimodal optimization, multiobjective optimization, dynamic optimization, and constrained optimization. However, there is no unified framework for constructing these types of problems and possible properties of many problems are not fully tunable. This will cause difficulties for researchers to analyze strengths and weaknesses of an algorithm. To address these issues, this paper proposes a simple and intuitive framework, which is able to construct different kinds of problems for continuous optimization. The framework utilizes the k-d tree to partition the search space and sets a certain number of simple functions in each subspace. The framework is implemented into global/multimodal optimization, dynamic single objective optimization, multiobjective optimization, and dynamic multiobjective optimization, respectively. Properties of the proposed framework are discussed and verified with traditional evolutionary algorithms.

• 出版日期2019-6
• 单位中国地质大学（北京）