Toward the Optimization of a Class of Black Box Optimization Algorithms

Many black box optimization algorithms have sufcient exibility to allow them to adapt to the varying circumstances they encounter. These capabilities are of two primary sorts: 1) user-determined choices among alternative parameters, operations, and logic structures, and 2) the algorithm-determined alternative paths chosen during the process of seeking a solution to a particular problem. This paper discusses the process of algorithm design and operation, with the intent of integrating the seemingly distinct aspects described above within a uni ed framework. We relate this algorithmic optimization process to the eld of dynamic process control. An approach is proposed toward the optimization of a process for controlling a speci c class of systems, and its application to dynamic adjustment of the algorithm used in the search problem. An instance of this approach in genetic algorithms is demonstrated. The experimental results show the adaptability and robustness of the proposed approach.

• Type: Conference
• Year: 1997
• Where: ICTAI
• Authors: Gang Wang, Erik D. Goodman, William F. Punch III
• Keywords: Algorithmic Optimization Process, Artificial Intelligence, Box Optimization Algorithms, Dynamic Process Control, ICTAI 1997