Optimisation algorithms are commonly compared on benchmarks to get insight into performance differences. However, it is not clear how closely benchmarks match the properties of real-world problems because these properties are largely unknown. This work investigates the properties of real-world problems through a questionnaire to enable the design of future benchmark problems that more closely resemble those found in the real world. The results, while not representative as they are based on only 45 responses, indicate that many problems possess at least one of the following properties: they are constrained, deterministic, have only continuous variables, require substantial computation times for both the objectives and the constraints, or allow a limited number of evaluations. Properties like known optimal solutions and analytical gradients are rarely available, limiting the options in guiding the optimisation process. These are all important aspects to consider when designing realistic benchmark problems. At the same time, the design of realistic benchmarks is difficult, because objective functions are often reported to be black-box and many problem properties are unknown. To further improve the understanding of real-world problems, readers working on a real-world optimisation problem are encouraged to fill out the questionnaire: https://tinyurl.com/opt-survey

翻译：优化算法通常在基准上比较,以洞察性能差异。然而,由于这些属性基本上不为人知,因此不清楚基准与现实世界问题的特点之间是否十分接近。这项工作通过问卷调查现实世界问题的性质,以便能够设计更接近现实世界发现的基准问题。结果虽然由于仅基于45份答复而没有代表性,但表明许多问题至少具有下列特性之一:它们受到制约,具有确定性,只有连续变量,需要大量计算目标和制约因素的时间,或允许数量有限的评价。诸如已知的最佳解决方案和分析梯度等属性很少可用,在指导优化进程时限制了选项。这些都是设计现实基准问题时需要考虑的重要方面。同时,现实基准的设计很困难,因为据报告,客观功能往往是黑箱,而且许多问题属性并不为人所知。为了进一步加深对现实世界问题的理解,鼓励从事现实世界优化问题的读者填写问卷:https://tinurl.com/opt-survey。