지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
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연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록· 키워드
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A robust optimization problem, which has a maximum function of continuously differentiable functions as its objective function, continuously differentiable functions as its constraint functions and a geometric constraint, is considered. We prove a necessary optimality theorem and a sufficient optimality theorem for the robust optimization problem. We formulate a Wolfe type dual problem for the robust optimization problem, which has a differentiable Lagrangean function, and establish the weak duality theorem and the strong duality theorem which hold between the robust optimization problem and its Wolfe type dual problem. Moreover, saddle point theorems for the robust optimization problem are given under convexity assumptions.
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참고문헌 (12)
참고문헌 신청
D. Bertsimas / 2009 / Constructing uncertainty sets for robust linear optimization / Oper. Res 57:1483~1495
A. Ben-Tal / 2002 / Robust optimization-methodology and applications / Math. Program. Ser. B 92:453~480
A. Ben-Tal / 2008 / A selected topics in robust convex optimization / Math. Program. Ser. B 112:125~158
D. Bertsimas / 2004 / Robust linear optimizaion under general norms / Oper. Res. Lett 32:510~516
A. Ben-Tal / 2009 / Robust optimization / Princeton Series in Applied Mathematics
A. Ben-Tal / 2002 / Robust optimization-methodology and applications / Math. Program. Ser. B 92:453~480
A. Ben-Tal / 2008 / A selected topics in robust convex optimization / Math. Program. Ser. B 112:125~158
D. Bertsimas / 2004 / Robust linear optimizaion under general norms / Oper. Res. Lett 32:510~516
A. Ben-Tal / 2009 / Robust optimization / Princeton Series in Applied Mathematics
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