A Location-Inventory Model for Large Three-Level Supply Chains

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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 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 ...

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 ...

In this thesis we address various factors that contribute both theoretically and practically to mitigating supply demand mismatches. The thesis is composed of three chapters, where each chapter is an independent scientific paper. In the first paper, we dev ...

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 ...

Omnichannel retail has emerged as the new standard in today's commerce landscape, with retailers integrating their physical and online channels to enhance the customer shopping experience. However, such integration presents significant challenges for retai ...

Making assortment decisions is becoming an increasingly difficult task for many retailers worldwide as they implement omnichannel initiatives. Discrete choice modeling lies at the core of this challenge, yet existing models do not sufficiently account for ...

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 ...

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 ...

Future low-carbon societies will need to store vast amounts of electricity to stabilize electricity grids and to power electric vehicles. Vehicle-to-grid allows vehicle owners and grid operators to share the costs of electricity storage by making the batte ...

In this paper, we analyze the recently proposed stochastic primal-dual hybrid gradient (SPDHG) algorithm and provide new theoretical results. In particular, we prove almost sure convergence of the iterates to a solution with convexity and linear convergenc ...

In this paper, we formulate a mixed integer linear program (MILP) for the simulated maximum likelihood estimation (MLSE) problem and devise a Benders decomposition approach to speed up the solution process. This framework can be applied to any advanced dis ...

We address for the first time the problem of correcting group discriminations within a score function, while minimizing the individual error. Each group is described by a probability density function on the set of profiles. We first solve the problem analy ...

The last few years have experienced the emergence of Industry 4.0 (I4.0), ultra-customization, and the explosion of demand for ethical, fair trade, and sustainable consumption. Organizations have therefore started a digital transformation of their SCs and ...

Globalization, outsourcing and cost optimization have all contributed to increased supply chain vulnerability, yet our understanding of effective mitigation strategies remains limited. In our research, we study the effects of disruptions on supply chain ne ...

This paper considers vessel scheduling with pilotage and tugging constraints in berthing operations with channel restrictions at seaports. To our knowledge, pilotage and tugging requirements have not been simultaneously considered in the literature. This w ...

In many transportation systems, a mismatch between the associated design and planning decisions and the demand is typically encountered. A tailored system is not only appealing to operators, which could have a better knowledge of their operational costs, b ...

The task of optimally designing and scheduling energy systems with a high share of renewable energies is complex and computationally demanding. A widespread method for tackling this task is to apply mixed integer linear programming (MILP). Even though the ...

A Location-Inventory Model for Large Three-Level Supply Chains

Chattez avec Graph Search

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

Learning to Remove Cuts in Integer Linear Programming

HYPERBOLA METHOD ON TORIC VARIETIES

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

Six-dimensional sphere packing and linear programming

Optimizing Sales Forecasting, Inventory, Pricing and Sourcing Decisions

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

Quantitative Methods for Omnichannel Decision-Making

Assortment optimization using an attraction model in an omnichannel environment

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

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Vehicle-to-Grid for Reliable Frequency Regulation

On The Convergence Of Stochastic Primal-Dual Hybrid Gradient

A Benders decomposition for maximum simulated likelihood estimation of advanced discrete choice models

Removing Algorithmic Discrimination (With Minimal Individual Error)

Industry 4.0 Technologies and Customer-centricity for Digital Supply Chains

Modeling Supply Chain Disruptions: A Network Flow Approach

Vessel scheduling with pilotage and tugging considerations

Integrating advanced discrete choice models in mixed integer linear optimization

Data reduction for mixed integer linear programming in complex energy systems