Inverse optimization for linearly constrained convex separable programming problems
作者： Jianzhong Zhang , Chengxian Xu
DOI: 10.1016/J.EJOR.2009.01.043
关键词:
摘要: Abstract In this paper, we study inverse optimization for linearly constrained convex separable programming problems that have wide applications in industrial and managerial areas. For a given feasible point of program, the is to determine whether can be made optimal by adjusting parameter values problem, when answer positive, find smallest adjustments. A sufficient necessary condition able become values. Inverse formulations are presented with l 1 2 norms. These either linear norm used formulation, or quadratic used.
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