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Proximal Point Algorithms for Convex Multi-criteria Optimization with Applications to Supply Chain Risk Management |
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| Authors: | Shao-Jian Qu Mark Goh Robert De Souza Tie-Nan Wang |
| Institution: | 1. Harbin Institute of Technology, Rm.519, Bldg.2H, 2 Yikuang Str., Nangang Dist., Harbin, 150080, People’s Republic of China 2. The Logistics Institute-Asia Pacific, National University of Singapore, Singapore, Singapore 3. Business School, National University of Singapore, Singapore, Singapore |
| Abstract: | We study a class of convex multi-criteria optimization problems with convex objective functions under linear constraints. We use a non-scalarization method—namely, two implementable proximal point algorithms—to obtain the Pareto optimum under multi-criteria optimization. We show that the algorithms are globally convergent. We apply the algorithms to a supply chain risk management problem under multi-criteria considerations. |
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