Solving the Partial Inverse Knapsack Problem

In this paper, we investigate the partial inverse knapsack problem, a bilevel optimization problem in which the follower solves a classical 0/1-knapsack problem with item profit values comprised of a fixed part and a modification determined by the leader. Specifically, the leader problem seeks a minimal change to given item profits such that there is … Read more

Extending the reflect flow formulation to variable-sized one-dimensional cutting and skiving stock problems

Flow formulations have been widely studied for the one-dimensional cutting stock problem and several of its extensions. Among these, the so-called reflect model has shown the best empirical performance when solved directly with a general-purpose integer linear programming solver due to its reduced number of variables and constraints. However, existing adaptations of reflect for the … Read more

The Minimization of the Weighted Completion Time Variance in a Single Machine: A Specialized Cutting-Plane Approach

This study addresses the problem of minimizing the weighted completion time variance (WCTV) in single-machine scheduling. Unlike the unweighted version, which has been extensively studied, the weighted variant introduces unique challenges due to the absence of theoretical properties that could guide the design of efficient algorithms. We propose a mathematical programming framework based on a … Read more

Recoverable Robust Cardinality Constrained Maximization with Commitment of a Submodular Function

We consider a game-theoretic variant of maximizing a monotone increasing, submodular function under a cardinality constraint. Initially, a solution to this classical problem is determined. Subsequently, a predetermined number of elements from the ground set, not necessarily contained in the initial solution, are deleted, potentially reducing the solution’s cardinality. If any deleted elements were part … Read more

Implied Integrality in Mixed-Integer Optimization

Implied-integer detection is a well-known presolving technique that is used by many Mixed-Integer Linear Programming solvers. Informally, a variable is said to be implied integer if its integrality is enforced implicitly by integrality of other variables and the constraints of a problem. In this work we formalize the definition of implied integrality by taking a … Read more

Strength of the Upper Bounds for the Edge-Weighted Maximum Clique Problem

We theoretically and computationally compare the strength of the two main upper bounds from the literature on the optimal value of the Edge-Weighted Maximum Clique Problem (EWMCP). We provide a set of instances for which the ratio between either of the two upper bounds and the optimal value of the EWMCP is unbounded. This result … Read more

Novel closed-loop controllers for fractional linear quadratic tracking systems

A new method for finding closed-loop optimal controllers of fractional tracking quadratic optimal control problems is introduced. The optimality conditions for the fractional optimal control problem are obtained. Illustrative examples are presented to show the applicability and capabilities of the method. ArticleDownload View PDF

Two approaches to piecewise affine approximation

The problem of approximation by piecewise affine functions has been studied for several decades (least squares and uniform approximation). If the location of switches from one affine piece to another (knots for univariate approximation) is known the problem is convex and there are several approaches to solve this problem. If the location of such switches … Read more

A Dantzig-Wolfe Single-Level Reformulation for Mixed-Integer Linear Bilevel Optimization: Exact and Heuristic Approaches

Bilevel optimization problems arise in numerous real-world applications. While single-level reformulations are a common strategy for solving convex bilevel problems, such approaches usually fail when the follower’s problem includes integer variables. In this paper, we present the first single-level reformulation for mixed-integer linear bilevel optimization, which does not rely on the follower’s value function. Our … Read more

SDP bounds on the stability number via ADMM and intermediate levels of the Lasserre hierarchy

We consider the Lasserre hierarchy for computing bounds on the stability number of graphs. The semidefinite programs (SDPs) arising from this hierarchy involve large matrix variables and many linear constraints, which makes them difficult to solve using interior-point methods. We propose solving these SDPs using the alternating direction method of multipliers (ADMM). When the second … Read more