Best practices for comparing optimization algorithms
Copyright policy )Best practices for comparing optimization algorithms
Comparing, or benchmarking, of optimization algorithms is a complicated task that involves many subtle considerations to yield a fair and unbiased evaluation. In this paper, we systematically review the benchmarking process of optimization algorithms, and discuss the challenges of fair comparison. We provide suggestions for each step of the comparison process and highlight the pitfalls to avoid when evaluating the performance of optimization algorithms. We also discuss various methods of reporting the benchmarking results. Finally, some suggestions for future research are presented to improve the current benchmarking process.
Algorithm comparison, Performance, Testing, 65K05, Guidelines, timing, FOS: Mathematics, Analysis of algorithms, algorithm comparison, Timing, benchmarking, guidelines, Metric, Abstract computational complexity for mathematical programming problems, F.2.1, G.1.6, Mathematics - Optimization and Control, software, metric, Optimization algorithms, testing, Benchmarking, Optimization and Control (math.OC), Computational methods for problems pertaining to operations research and mathematical programming, optimization algorithms, Software, performance
Algorithm comparison, Performance, Testing, 65K05, Guidelines, timing, FOS: Mathematics, Analysis of algorithms, algorithm comparison, Timing, benchmarking, guidelines, Metric, Abstract computational complexity for mathematical programming problems, F.2.1, G.1.6, Mathematics - Optimization and Control, software, metric, Optimization algorithms, testing, Benchmarking, Optimization and Control (math.OC), Computational methods for problems pertaining to operations research and mathematical programming, optimization algorithms, Software, performance
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