On the Robust Knapsack Problem

We consider an uncertain variant of the knapsack problem that arises when the exact weight of each item is not exactly known in advance but belongs to a given interval, and the number of items whose weight differs from the nominal value is bounded by a constant. We analyze the worsening of the optimal solution … 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

Recoverable Robust Knapsacks: $\GammahBcScenarios

In this paper, we investigate the recoverable robust knapsack problem, where the uncertainty of the item weights follows the approach of Bertsimas and Sim (2003,2004). In contrast to the robust approach, a limited recovery action is allowed, i.e., upto k items may be removed when the actual weights are known. This problem is motivated by … Read more

Recoverable Robust Knapsack: the Discrete Scenario Case

Admission control problems have been studied extensively in the past. In a typical setting, resources like bandwidth have to be distributed to the different customers according to their demands maximizing the profit of the company. Yet, in real-world applications those demands are deviating and in order to satisfy their service requirements often a robust approach … Read more

Integer Solutions to Cutting Stock Problems

We consider two integer linear programming models for the one-dimensional cutting stock problem that include various difficulties appearing in practical real problems. Our primary goals are the minimization of the trim loss or the minimization of the number of master rolls needed to satisfy the orders. In particular, we study an approach based on the … Read more

Stochastic binary problems with simple penalties for capacity constraints violations

This paper studies stochastic programs with first-stage binary variables and capacity constraints, using simple penalties for capacities violations. In particular, we take a closer look at the knapsack problem with weights and capacity following independent random variables and prove that the problem is weakly \NP-hard in general. We provide pseudo-polynomial algorithms for three special cases … Read more

The Knapsack Problem with Conflict Graphs

We extend the classical 0-1 knapsack problem by introducing disjunctive constraints for pairs of items which are not allowed to be packed together into the knapsack. These constraints are represented by edges of a conflict graph whose vertices correspond to the items of the knapsack problem. Similar conditions were treated in the literature for bin … Read more

Maximizing Non-monotone Submodular Functions under Matroid and Knapsack Constraints

Submodular function maximization is a central problem in combinatorial optimization, generalizing many important problems including Max Cut in directed/undirected graphs and in hypergraphs, certain constraint satisfaction problems, maximum entropy sampling, and maximum facility location problems. Unlike submodular minimization, submodular maximization is NP-hard. In this paper, we give the first constant-factor approximation algorithm for maximizing any … Read more

New Turnpike Theorems for the Unbounded Knapsack Problem

We develop sharp bounds on turnpike theorems for the unbounded knapsack problem. Turnpike theorems specify when it is optimal to load at least one unit of the best item (i.e., the one with the highest “bang-for-buck” ratio) and, thus can be used for problem preprocessing. The successive application of the turnpike theorems can drastically reduce … Read more