A SVM-based Method for Engine Maintenance Strategy Optimization

— Due to the abundant application background, the optimization of maintenance problem has been extensively studied in the past decades. Besides the well-known difficulty of large state space and large action space, the pervasive application of digital computers forces us to consider the new constraint of limited memory space. The given memory space restricts what strategies can be explored during the optimization procedure. By explicitly quantifying the minimal memory space to store a strategy using support vector machine, we propose to describe simple strategies exactly and only approximate complex strategies. This selective approximation can best utilize the given memory space for any description mechanism. We use numerical results on illustrative examples to show how the selective approximation improves the solution quality. We hope this work sheds some insights to best utilize the memory space for practical engine maintenance strategy optimization problems.

• Type: Conference
• Year: 2006
• Where: ICRA
• Authors: Qing-Shan Jia, Qianchuan Zhao
• Keywords: ICRA 2006, Limited Memory Space, Memory Space, Minimal Memory Space, Robotics