New-generation optimization algorithms for engineering

该候选人与不列颠哥伦比亚大学（CA）建立了新的合作关系，其中包括在他共同指导下的一名博士生的讨论，从而产生了预印本[1]。此外，他还受邀访问东京工业大学（2022年12月）、比萨大学（计划于2023年5月）和重庆师范大学（计划于2023年8月）。他的研究趋势延续了前一年的路线，并将更多的注意力集中在凸优化的无线研究方法[2]和电网扩展规划的（凸）优化[4]上。与过去一样，对凸领域的第一次研究意味着作为潜在的非凸扩展的基础，这是本建议的最终目标王忠，AT, Ou H，和王x。张建军，张建军，张建军，等。一种镜面惯性前反射-后反射分裂：全局收敛和超越凸性和Lipschitz平滑的直线研究[j] .光子学报，2014,29(4):951 - 951。张建军，张建军，张建军，等。梯度局部Lipschitz连续性下凸优化的自适应近端算法[j] .中文信息学报：自然科学版，2011,31(4):551 - 551。中国石油大学学报（自然科学版），第1期，第3期，2023

The candidate established a new collaboration with the University of British Columbia (CA), including in the discussion a PhD student under his co-supervision that resulted in the preprint [1]. In addition, he has been invited for visiting periods at the Tokyo Institute of Technology (December 2022), the University of Pisa (scheduled for May 2023), and the Chongqing Normal University (scheduled for August 2023). His research trend continues along the lines of the previous year, with additional focus on linesearch-free methods for convex optimization [2] and (convex) optimization for power-grid expansion planning [4]. As in the past, a first inquiry in the convex realm is meant to serve as foundation for potential nonconvex extensions, ultimate target of the proposal.[1] Z Wang, AT, H Ou, and X Wang. A mirror inertial forward-reflected-backward splitting: Global convergence and linesearch extension beyond convexity and Lipschitz smoothness, arXiv:2212.01504, 2022[2] P Latafat, AT, L Stella, and P Patrinos. Adaptive proximal algorithms for convex optimization under local Lipschitz continuity of the gradient, arXiv:2301.04431, 2023[3] S Hardy, AT, K Yamamoto, H Ergun, and D Van Hertem. Optimal grid layouts for hybrid offshore assets in the North Sea under different market designs, arXiv:2301.00931, 2023