Stackelberg Games with k-Submodular Function under Distributional Risk-Receptiveness and Robustness

\(\) We study submodular optimization in adversarial context, applicable to machine learning problems such as feature selection using data susceptible to uncertainties and attacks. We focus on Stackelberg games between an attacker (or interdictor) and a defender where the attacker aims to minimize the defender’s objective of maximizing a k-submodular function. We allow uncertainties arising … Read more

Stabilizing GNEP-Based Model Predictive Control: Quasi-GNEPs and End Constraints

We present a feedback scheme for non-cooperative dynamic games and investigate its stabilizing properties. The dynamic games are modeled as generalized Nash equilibrium problems (GNEP), in which the shared constraint consists of linear time-discrete dynamic equations (e.g., sampled from a partial or ordinary differential equation), which are jointly controlled by the players’ actions. Further, the … Read more

Strict efficiency in set optimization studied with the set approach

This paper is devoted to strict efficiency in set optimization studied with the set approach. Strict efficient solutions are defined with respect to the $l$-type less order relation and the possibly less order relation. Scalar characterization and necessary and/or sufficient conditions for such solutions are obtained. In particular, we establish some conditions expressed in terms … Read more

On Necessary Optimality Conditions for Sets of Points in Multiobjective Optimization

Taking inspiration from what is commonly done in single-objective optimization, most local algorithms proposed for multiobjective optimization extend the classical iterative scalar methods and produce sequences of points able to converge to single efficient points. Recently, a growing number of local algorithms that build sequences of sets has been devised, following the real nature of … Read more

On the accurate detection of the Pareto frontier for bi-objective mixed integer linear problems

We propose a criterion space search algorithm for bi-objective mixed integer linear programming problems. The Pareto frontier of these problems can have a complex structure, as it can include isolated points, open, half-open and closed line segments. Therefore, its exact detection is an achievable though hard computational task. Our algorithm works by alternating the resolution … Read more

Scheduling Bodyguards

Security agencies throughout the world use bodyguards to protect government officials and public figures. In this paper, we consider a two-person zero-sum game between a defender who allocates such bodyguards to protect several targets and an attacker who chooses one target to attack. Because the number of feasible bodyguard allocations grows quickly as either the … Read more

Freight consolidation through carrier collaboration – A cooperative game

Reducing inefficient truck movements, this research investigates the potential of freight consolidation through carrier collaboration. Considering the financial benefits of consolidation and the additional cost arising from collaboration, we propose a cooperative game to explore under which circumstances carriers can collaborate. We show that stable cost allocations are not always possible, affecting stability and thus … Read more

Considering homeowner acceptance of retrofit measures within energy supply network optimization

A key factor towards a low-carbon society is energy efficient heating of private houses. The choice of heating technology as well as the decision for certain energy-efficient house renovations are made mainly by individual homeowners. In contrast, municipal energy network planning heavily depends on and strongly affects these decisions. Further, there are different conflicting objectives … Read more

A Subspace Minimization Barzilai-Borwein Method for Multiobjective Optimization Problems

Nonlinear conjugate gradient methods have recently garnered significant attention within the multiobjective optimization community. These methods aim to maintain consistency in conjugate parameters with their single-objective optimization counterparts. However, the preservation of the attractive conjugate property of search directions remains uncertain, even for quadratic cases, in multiobjective conjugate gradient methods. This loss of interpretability of … Read more

A Parametric Approach for Solving Convex Quadratic Optimization with Indicators Over Trees

This paper investigates convex quadratic optimization problems involving $n$ indicator variables, each associated with a continuous variable, particularly focusing on scenarios where the matrix $Q$ defining the quadratic term is positive definite and its sparsity pattern corresponds to the adjacency matrix of a tree graph. We introduce a graph-based dynamic programming algorithm that solves this … Read more