Results 101 to 110 of about 3,492,516 (198)

Multi-objective worst case optimization by means of evolutionary algorithms [PDF]

open access: yes
Many real-world optimization problems are subject to uncertainty. A possible goal is then to find a solution which is robust in the sense that it has the best worst-case performance over all possible scenarios.
Avigad, Gideon   +2 more
core  

Discrete Convexity and Dynamic Robust Optimization

open access: yes, 2018
We discuss necessary and sufficient conditions for the optimality of specific classes of policies in dynamic robust optimization. We then focus on the specific case of affine policies, and show how our conditions can be used to recover and generalize ...
Iancu, Dan
core   +1 more source

Distributionally Robust Optimization with Principal Component Analysis

open access: yes, 2019
In this talk, we propose a new approximation method to solve distributionally robust optimization problems with moment-based ambiguity sets.
Cheng, JianQiang
core   +1 more source

From Data to Decisions: Distributionally Robust Optimization is Optimal

open access: yes, 2018
Data-driven stochastic programming aims to find a procedure that transforms time series data to a near-optimal decision (a prescriptor) and to a prediction of this decision's expected cost under the unknown data-generating distribution (a predictor).
Kuhn, Daniel
core   +1 more source

平面连杆机构的6σ稳健优化设计

open access: yesJixie chuandong, 2011
In the deterministic optimization design of planar linkage,the optimal solution which meets various constraints is generally close to constraint boundary.With random fluctuation of variables,the optimal solution tends to become infeasible solution ...
潘金坤
doaj  

Measuring the Value of Randomized Solutions in Distributionally Robust Optimization

open access: yes, 2018
This talk studies the value of randomized solutions (VRS) in distributionally robust mixed integer programming problems. We show different methods for obtaining upper bounds on VRS and identify conditions under which some of them are tight.
Delage, Erick
core   +1 more source

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