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A practicable framework for distributionally robust linear optimization Dimitris Bertsimas Massachusetts Institute of Technology Melvyn Sim, Meilin Zhang NUS Business School, National University of Singapore We developed a modular framework to obtain exact and approximate solutions to a class of linear optimiza- tion problems with recourse with the goal to minimize the worst-case …
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Introduction to Linear Optimization Dimitris Bertsimas John N. Tsitsiklis Massachusetts Institute of Technology Athena Scientific, Belmont, Massachusetts . Contents Preface xi 1. Introduction 1 1.1. Variants of the linear programming problem 2 1.2. Examples of linear programming problems 6 1.3. Piecewise linear convex objective functions 15 1.4. Graphical representation and solution 21 1.5
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<n+1) is a degenerate basic feasible solution in Q; show the example in a figure. (b) Show that the zero vector (in < n+1 ) minimizes (c,0) 0 y over all y ∈ Q if and only if the optimal cost in the original linear programming problem is greater
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A practicable framework for distributionally robust linear optimization Dimitris Bertsimas Massachusetts Institute of Technology Melvyn Sim, Meilin Zhang NUS Business School, National University of Singapore We developed a modular framework to obtain exact and approximate solutions to a class of linear optimiza-tion problems with recourse with the goal to minimize the worst-case …
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