DC programming and DCA: thirty years of developments

• 成果类型: Article
• 署名作者: Hoai An Le Thi; Tao Pham Dinh
• 署名单位: Universite de Lorraine
• 刊物名称: MATHEMATICAL PROGRAMMING
• ISSN/ISSBN: 0025-5610
• DOI: 10.1007/s10107-018-1235-y
• 发表日期: 2018
• 页码: 5-68
• 关键词: Support vector machines; nonconcave penalized likelihood; balanced boolean functions; feature-selection; Nonconvex Optimization; variable selection; routing problem; Portfolio optimization; thresholding algorithm; efficient algorithm

摘要

The year 2015 marks the 30th birthday of DC (Difference of Convex functions) programming and DCA (DC Algorithms) which constitute the backbone of nonconvex programming and global optimization. In this article we offer a short survey on thirty years of developments of these theoretical and algorithmic tools. The survey is comprised of three parts. In the first part we present a brief history of the field, while in the second we summarize the state-of-the-art results and recent advances. We focus on main theoretical results and DCA solvers for important classes of difficult nonconvex optimization problems, and then give an overview of real-world applications whose solution methods are based on DCA. The third part is devoted to new trends and important open issues, as well as suggestions for future developments.