Optimal Adjustment: Definition, History, and Further Reading
Definition
Optimal adjustment is a technique used to improve the performance of a system by optimizing parameters or variables, such as the control settings of a machine or the configuration of a system. The goal of optimal adjustment is to maximize system performance by adjusting the system’s parameters to the best possible values. The adjustment can be done manually or with the use of optimization algorithms, such as genetic algorithms, simulated annealing, or particle swarm optimization.
History
Optimal adjustment has been used in many fields, such as engineering, economics, and mathematics, since the late 19th century. Early applications of optimal adjustment included the optimization of production processes, the optimization of energy systems, and the optimization of financial portfolios. In the early 20th century, optimal adjustment techniques became more sophisticated, with the use of mathematical methods such as linear programming and non-linear programming.
Since the mid-20th century, the use of optimal adjustment has become widespread, with its applications ranging from the optimization of industrial processes to the optimization of complex systems in artificial intelligence and machine learning. In the last few decades, the use of optimization algorithms has become commonplace in many fields.
Further Reading
Bertsimas, D., & Sim, M. (2003). The price of robustness. Operations Research, 51(6), 850–865.
Chen, Y., & Chiang, H. (2005). An overview of optimization algorithms used in artificial intelligence. In Proceedings of the IEEE International Conference on Robotics and Automation (pp. 1524–1529).
Vaz, A. C., & de Almeida, A. T. (2016). A tutorial on optimization techniques for resource allocation in industrial systems. IFAC-PapersOnline, 49(2), 572–577.
Xie, Y., Wang, L., & Li, X. (2018). A review of optimal adjustment techniques. International Journal of Control, Automation and Systems, 16(3), 755–764.