Manual Optimization of Ill-Structured Problems
James R. Buck, Walton M. Hancock · Proceedings of the Human Factors and Ergonomics Society Annual Meeting · 1975
This paper describes an empirical study on human operators optimizing ill-structured problems over a variety of problem conditions. Performance and exploratory characteristics of the operators were examined as a function of these conditions relative to the random automatic optimization method. Manual optimization performance exceeded that of the automatic method under most conditions. In those problems containing more controls to be optimized and where there were few trials available, manual optimization was far more effective. Operator performance was impaired in solving problems which contained noise in the reported pay-off. Exploratory characteristics of these operators changed with the problem conditions. Based upon these characteristics, manual optimization may be described as a low-order gradient optimizer with adaptation to different problem conditions.