A Polyhedral Study of the Semi-Continuous Knapsack Problem

We study the convex hull of the feasible set of the semi-continuous knapsack problem, in which the variables belong to the union of two intervals. Besides being important in its own right, the semi-continuous knapsack problem arises in a number of other contexts, e.g. it is a relaxation of general mixed-integer programming. We show how … Read more

Sampling Decisions in Optimum Experimental Design in the Light of Pontryagin’s Maximum Principle

Optimum Experimental Design (OED) problems are optimization problems in which an experimental setting and decisions on when to measure – the so-called sampling design – are to be determined such that a follow-up parameter estimation yields accurate results for model parameters. In this paper we use the interpretation of OED as optimal control problems with … Read more

Branch-and-Cut for Separable Piecewise Linear Optimization: New Inequalities and Intersection with Semi-Continuous Constraints

We give new facets and valid inequalities for the separable piecewise linear optimization knapsack polytope. We also extend the inequalities to the case in which some of the variables are semi-continuous. In a companion paper (de Farias, Gupta, Kozyreff, Zhao, 2011) we demonstrate the efficiency of the inequalities when used as cuts in a branch-and-cut … Read more

Branch-and-Cut for Separable Piecewise Linear Optimization: Computation

We report and analyze the results of our extensive computational testing of branch-and-cut for piecewise linear optimization using the cutting planes given recently by Zhao and de Farias. Besides analysis of the performance of the cuts, we also analyze the effect of formulation on the performance of branch-and-cut. Finally, we report and analyze initial results … Read more

An algorithm for the separation of two-row cuts

We consider the question of finding deep cuts from a model constructed with two rows of a simplex tableau. To do that, we show how to reduce the complexity of setting up the polar of such model from a quadratic number of integer hull computations to a linear number of integer hull computations. Furthermore we … Read more

An Exact Penalty Global Optimization Approach for Mixed-Integer Programming Problems

In this work, we propose a global optimization approach for mixed-integer programming problems. To this aim, we preliminarily de ne an exact penalty algorithm model for globally solving general problems and we show its convergence properties. Then, we describe a particular version of the algorithm that solves mixed integer problems. Citation DIS Technical Report n. 17, … Read more

Two-Stage Robust Power Grid Optimization Problem

Under the deregulated energy market environment, plus the integration of renewable energy generation, both the supply and demand of a power grid system are volatile and under uncertainty. Accordingly, a large amount of spinning reserve is required at each bus to maintain the reliability of the power grid system in the traditional approach. In this … Read more

An Empirical Evaluation of Walk-and-Round Heuristics for Mixed-Integer Linear Programs

Geometric random walks have been proposed and analyzed for solving optimization problems. In this paper we report our computational experience with generating feasible integer solutions of mixed-integer linear programs using geometric random walks, and a random ray approach. A feasibility pump is used to heuristically round the generated points. Computational results on MIPLIB2003 and COR@L … Read more

New concave penalty functions for improving the Feasibility Pump

Mixed-Integer optimization represents a powerful tool for modeling many optimization problems arising from real-world applications. The Feasibility pump is a heuristic for finding feasible solutions to mixed integer linear problems. In this work, we propose a new feasibility pump approach using concave non-differentiable penalty functions for measuring solution integrality. We present computational results on binary … Read more

A probabilistic comparison of split and type 1 triangle cuts for two row mixed-integer programs

We provide a probabilistic comparison of split and type 1 triangle cuts for mixed-integer programs with two rows and two integer variables. Under a simple probabilistic model of the problem parameters, we show that a simple split cut, i.e. a Gomory cut, is more likely to be better than a type 1 triangle cut in … Read more