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This paper offers a new algorithm to efficiently optimize scheduling decisions for dial-a-ride problems (DARPs), including problem variants considering electric and autonomous vehicles (e-ADARPs). The scheduling heuristic, based on linear programming theor ...

Cutting plane methods are a fundamental approach for solving integer linear programs (ILPs). In each iteration of such methods, additional linear constraints (cuts) are introduced to the constraint set with the aim of excluding the previous fractional opti ...

We prove that the Cohn-Elkies linear programming bound for sphere packing is not sharp in dimension 6. The proof uses duality and optimization over a space of modular forms, generalizing a construction of Cohn- Triantafillou [Math. Comp. 91 (2021), pp. 491 ...

We develop a very general version of the hyperbola method which extends the known method by Blomer and Brudern for products of projective spaces to complete smooth split toric varieties. We use it to count Campana points of bounded log-anticanonical height ...

In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...

This paper rethinks Sharpness-Aware Minimization (SAM), which is originally formulated as a zero-sum game where the weights of a network and a bounded perturbation try to minimize/maximize, respectively, the same differentiable loss. We argue that SAM shou ...

An integer linear program is a problem of the form max{c^T x : Ax=b, x >= 0, x integer}, where A is in Z^(n x m), b in Z^m, and c in Z^n. Solving an integer linear program is NP-hard in general, but there are several assumptions for which it becomes fixed ...

We present the Breakpoint Exact Algorithm (BEA) together with a Spatial Branch and Bound (B&B), and Spatial Branch and Benders Decomposition (B&BD) approach to tackle the uncapacitated choice-based pricing problem (CPP) where demand is captured by a disc ...

In this paper, we present a spatial branch and bound algorithm to tackle the continuous pricing problem, where demand is captured by an advanced discrete choice model (DCM). Advanced DCMs, like mixed logit or latent class models, are capable of modeling de ...

The decentralisation and unpredictability of new renewable energy sources require rethinking our energy system. Data-driven approaches, such as reinforcement learning (RL), have emerged as new control strategies for operating these systems, but they have n ...

Non-convex constrained optimization problems have become a powerful framework for modeling a wide range of machine learning problems, with applications in k-means clustering, large- scale semidefinite programs (SDPs), and various other tasks. As the perfor ...

In this thesis, we unveil a third design path to manipulate elastic waves within architected media, distinct from the traditional phononic crystal and locally-resonant metamaterial concepts. The core innovation lies in the concept of nonlocal resonances, d ...

In this thesis, we give new approximation algorithms for some NP-hard problems arising in resource allocation and network design. As a resource allocation problem, we study the Santa Claus problem (also known as the MaxMin Fair Allocation problem) in which ...

The shipping industry was responsible for about 3% of global greenhouse gas (GHG) emissions in 2018. In this context, the International Maritime Organisation (IMO) has established stringent targets to reduce GHG emissions by at least 50% by 2050 compared t ...

Control systems operating in real-world environments often face disturbances arising from measurement noise and model mismatch. These factors can significantly impact the perfor- mance and safety of the system. In this thesis, we aim to leverage data to de ...

We use numerical bootstrap techniques to study correlation functions of traceless sym-metric tensors of O(N) with two indices ti j. We obtain upper bounds on operator dimen-sions for all the relevant representations and several values of N. We discover sev ...

A graph H is a minor of a second graph G if G can be transformed into H by two operations: 1) deleting nodes and/or edges, or 2) contracting edges. Coarse-grained reconfigurable array (CGRA) application mapping is closely related to the graph minor problem ...

Time-sensitive networks, as in the context of IEEE Time-Sensitive Networking (TSN) and IETF Deterministic Networking (DetNet), offer deterministic services with guaranteed bounded latency in order to support safety-critical applications. In this thesis, we ...

In the current era of big data, aggregation queries on high-dimensional datasets are frequently utilized to uncover hidden patterns, trends, and correlations critical for effective business decision-making. Data cubes facilitate such queries by employing p ...

Correlated errors of experimental data are a common but often neglected problem in physical sciences. Various tools are provided here for thorough propagation of uncertainties in cases of correlated errors. Discussed are techniques especially applicable to ...

Vectors in a box

Chattez avec Graph Search

A ride time-oriented scheduling algorithm for dial-a-ride problems

Learning to Remove Cuts in Integer Linear Programming

Six-dimensional sphere packing and linear programming

HYPERBOLA METHOD ON TORIC VARIETIES

Quantifying the Unknown: Data-Driven Approaches and Applications in Energy Systems

Improving SAM Requires Rethinking its Optimization Formulation

Results on Sparse Integer Programming and Geometric Independent Sets

Exact Algorithms for Continuous Pricing with Advanced Discrete Choice Demand Models

A Spatial Branch and Bound Algorithm for Continuous Pricing with Advanced Discrete Choice Demand Modeling

Reinforcement Learning for Joint Design and Control of Battery-PV Systems

Augmented Lagrangian Methods for Provable and Scalable Machine Learning

Nonlocally-resonant metamaterials

Approximation Algorithms for Allocation and Network Design

Hybridisation Scenarios of Solid Oxide Fuel Cells, Batteries, and Internal Combustion Engines for Waterborne Transportation

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Bootstrapping traceless symmetric O(N) scalars

GRAMM: Fast CGRA Application Mapping Based on A Heuristic for Finding Graph Minors

Worst-Case Delay Analysis of Time-Sensitive Networks with Network Calculus

Interactive-time Exploration, Querying, and Analysis of Large High-dimensional Datasets

Reliable uncertainties: Error correlation, rotated error bars, and linear regressions in three-isotope plots and beyond