A Design of Global Optimization System for Signomial Programming Problems

• Main Authors: Nian-Ze Hu, 胡念祖
• Other Authors: Han-Lin Li
• Format: Others
• Language: en_US
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/56869341818699432894

博士 === 國立交通大學 === 資訊管理研究所 === 92 === Signomial programming techniques have been applied in many areas such as Engineering Design, Financial planning and Transportation. Deterministic and heuristic approaches are two popular methods to deal with the Signomial programming problem. Either of the two methods has its own strengths and weaknesses. This study proposes a framework integrating deterministic programming approaches (e.g., convexification and piecewise linearization) and heuristic approaches (e.g., genetic algorithm). Furthermore, the proposed system is enhanced by several refurbished algorithms. The core of the proposed system is a distributed processing mechanism which decomposes the problem into independent pieces. Distributes these sub problems to a group of available personal computers, and compare the solutions found by these individual computers to conclude the globally optimal solution for the generalized signomial problems. In sum, the proposed system contributes to the current literature in the following aspects: 1. Compared to traditional deterministic approaches, the new system can handle problems with higher efficiency. 2. Relative to heuristic approaches which suffer from instable solution quality, it can guarantee solutions with better quality. 3. The proposed distributed processing mechanism is OS independent with incredible cost-savings compared to the currently available parallel processing system. 4. The system integrates existent high-performance optimization software packages, which enables it to handle more general problems in a stable and efficient manner.