Guest Editorial Special Issue on Benchmarking Sampling-Based Optimization Heuristics: Methodology and Software

IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION(2022)

引用 1|浏览16
暂无评分
摘要
Benchmarking provides an essential ground base for adequately assessing and comparing evolutionary computation methods and other optimization algorithms. It allows us to gain insights into strengths and weaknesses of different existing techniques, and consequently design more efficient optimization approaches. The need for good benchmarking practices opens up a broad range of complementary research questions, arising as a byproduct of challenges encountered when optimization methods are assessed. From the selection of representative benchmark problem instances, different algorithms, and suitable performance metrics, over efficient experimentation, to a sound evaluation of the benchmark data, these research questions lie at the core of establishing a well-designed and standardized benchmarking procedure.
更多
查看译文
关键词
optimization,sampling-based
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要