Pascal Halffmann
YOU?
Author Swipe
View article: Enhancing Variational Quantum Algorithms for Multicriteria Optimization
Enhancing Variational Quantum Algorithms for Multicriteria Optimization Open
This paper presents methodological improvements to variational quantum algorithms (VQAs) for solving multicriteria optimization problems. We introduce two key contributions. First, we reformulate the parameter optimization task of VQAs as …
View article: Risk management in multi-objective portfolio optimization under uncertainty
Risk management in multi-objective portfolio optimization under uncertainty Open
In portfolio optimization, decision makers face difficulties from uncertainties inherent in real-world scenarios. These uncertainties significantly influence portfolio outcomes in both classical and multi-objective Markowitz models. To add…
View article: Harnessing Inferior Solutions For Superior Outcomes: Obtaining Robust Solutions From Quantum Algorithms
Harnessing Inferior Solutions For Superior Outcomes: Obtaining Robust Solutions From Quantum Algorithms Open
In the rapidly advancing domain of quantum optimization, the confluence of\nquantum algorithms such as Quantum Annealing (QA) and the Quantum Approximate\nOptimization Algorithm (QAOA) with robust optimization methodologies presents a\ncut…
View article: Quadratic Unconstrained Binary Optimization Approach for Incorporating Solvency Capital into Portfolio Optimization
Quadratic Unconstrained Binary Optimization Approach for Incorporating Solvency Capital into Portfolio Optimization Open
In this paper, we consider the inclusion of the solvency capital requirement (SCR) into portfolio optimization by the use of a quadratic proxy model. The Solvency II directive requires insurance companies to calculate their SCR based on th…
View article: Analysis of the weighted Tchebycheff weight set decomposition for multiobjective discrete optimization problems
Analysis of the weighted Tchebycheff weight set decomposition for multiobjective discrete optimization problems Open
Scalarization is a common technique to transform a multiobjective optimization problem into a scalar-valued optimization problem. This article deals with the weighted Tchebycheff scalarization applied to multiobjective discrete optimizatio…
View article: NP-hard but no longer hard to solve? Using quantum computing to tackle optimization problems
NP-hard but no longer hard to solve? Using quantum computing to tackle optimization problems Open
In the last decade, public and industrial research funding has moved quantum computing from the early promises of Shor’s algorithm through experiments to the era of noisy intermediate scale quantum devices (NISQ) for solving real-world pro…
View article: NP-hard but no longer hard to solve? Using quantum computing to tackle optimization problems
NP-hard but no longer hard to solve? Using quantum computing to tackle optimization problems Open
In the last decade, public and industrial research funding has moved quantum computing from the early promises of Shor's algorithm through experiments to the era of noisy intermediate scale quantum devices (NISQ) for solving real-world pro…
View article: A Quantum Computing Approach for the Unit Commitment Problem
A Quantum Computing Approach for the Unit Commitment Problem Open
Planning energy production is a challenging task due to its cost-sensitivity, fast-moving energy markets, uncertainties in demand, and technical constraints of power plants. Thus, more complex models of this so-called \emph{unit commitment…
View article: Exact algorithms for multiobjective linear optimization problems with integer variables: A state of the art survey
Exact algorithms for multiobjective linear optimization problems with integer variables: A state of the art survey Open
We provide a comprehensive overview of the literature of algorithmic approaches for multiobjective mixed‐integer and integer linear optimization problems. More precisely, we categorize and display exact methods for multiobjective linear pr…
View article: An inner approximation method to compute the weight set decomposition of a triobjective mixed-integer problem
An inner approximation method to compute the weight set decomposition of a triobjective mixed-integer problem Open
This article is dedicated to the weight set decomposition of a multiobjective (mixed-)integer linear problem with three objectives. We propose an algorithm that returns a decomposition of the parameter set of the weighted sum scalarization…
View article: A general approximation method for bicriteria minimization problems
A general approximation method for bicriteria minimization problems Open
View article: Approximation schemes for the parametric knapsack problem
Approximation schemes for the parametric knapsack problem Open
View article: On the Online Min-Wait Relocation Problem
On the Online Min-Wait Relocation Problem Open