Hybrid optimization using DIRECT, GA, and SQP for global exploration

— As there are many good optimization algorithms each with its own characteristics, it is very difficult to choose the best method for optimization problems. Thus, it is important to select and apply the appropriate algorithms according to the complexities of the problem. However, it is difficult to solve very complicated problems with only a single algorithm, and a hybrid optimization approach, which combines multiple optimization algorithms, is necessary. To develop an efficient hybrid optimization algorithm, it is necessary to determine how the optimization process is performed. This paper focuses on the balance between local and broad searches. Multiple optimization methods are controlled to derive both the optimum point and the information of the landscape. To achieve the proposed optimization strategy, three distinguished optimization algorithms are introduced: DIRECT (DIviding RECTangles), GAs (Genetic Algorithms), and SQP (Sequential Quadratic Programming). To integrate th...

• Type: Conference
• Year: 2007
• Where: CEC
• Authors: Satoru Hiwa, Tomoyuki Hiroyasu, Mitsunori Miki
• Keywords: Artificial Intelligence, CEC 2007, Hybrid Optimization, Multiple Optimization, Optimization Algorithms