瀋　迅SHEN Xunシン　ジン

業績情報

氏名・連絡先

• 氏名

  シン　ジン, 瀋　迅, SHEN Xun

主たる所属・職名

• 工学研究院　先端電気電子部門, 准教授

学位

• 博士（機械工学）
  上智大学
  2018年03月31日

論文

• Approximate Uncertain Program
  Shen, Xun; Zhuang, Jiancang; Zhang, Xingguo
  IEEE ACCESS
  IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
  Chance constrained program where one seeks to minimize an objective over decisions which satisfy randomly disturbed constraints with a given probability is computationally intractable. This paper proposes an approximate approach to address chance constrained program. Firstly, a single layer neural-network is used to approximate the function from decision domain to violation probability domain. The algorithm for updating parameters in single layer neural-network adopts sequential extreme learning machine. Based on the neural violation probability approximate model, a randomized algorithm is then proposed to approach the optimizer in the probabilistic feasible domain of decision. In the randomized algorithm, samples are extracted from decision domain uniformly at first. Then, violation probabilities of all samples are calculated according to neural violation probability approximate model. The ones with violation probability higher than the required level are discarded. The minimizer in the remained feasible decision samples is used to update sampling policy. The policy converges to the optimal feasible decision. Numerical simulations are implemented to validate the proposed method for non-convex problems comparing with scenario approach and parallel randomized algorithm. The results show that proposed method have improved performance.
  2019年, 研究論文（学術雑誌）, 共同, 7, 2169-3536, DOI(公開)(r-map), 182357, 182365