The Development of Optimization in System Dynamics: Using Genetic Algorithm for Objective Function Combination

• Main Authors: Cheng-Yu Tasi, 蔡承祐
• Other Authors: Chia-Ping Chen
• Format: Others
• Language: zh-TW
• Published: 2005
• Online Access: http://ndltd.ncl.edu.tw/handle/73576296031396200013

碩士 === 國立屏東科技大學 === 資訊管理系 === 93 === When people face the problem, they will think about it with Reductionism or Attribution Theory. But here is the world of high complex, nonlinear. We can't solve problem only with Reductionism or Attribution no more. Because upon reason, we can use a concept of System Dynamics with dynamic complexity, causal relationship, feedback loop, nonlinear relationship and time delay to think about problem and solve problem. System Dynamics make people know the structure of system and then control the behavior of system. For historical reasons, optimization has traditionally been slightly outside the mainstream of system dynamics. Some scholar had experience can make a better strategic. But for new System Dynamics user, there is no principle to follow. In the past, the research on optimization of System Dynamics stress more in numerical adjust than Objective Function selection. This paper is using Genetic Algorithm to select the better Objective Function. The better Object Function combination will tell policymaker should make effort to what objective combination, and they will get the most benefit.