What Players do with the Ball: A Physically Constrained Interaction Modeling

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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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

The electrification of private mobility is becoming a popular solution to reduce the reliance on fossil fuels. However, uncontrollable charging of a large electric vehicle fleet challenges the distribution grid due to transmission bottlenecks, voltage limi ...

Designing structures from reused elements is becoming an increasingly important design task for structural engineers as it has potential to significantly reduce adverse environmental impacts of building structures. To allow for a broad application of this ...

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 ...

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 ...

The advancements in genome editing techniques over the past years have rekindled interest in rational metabolic engineering strategies. While Metabolic Control Analysis (MCA) is a well-established method for quantifying the effects of metabolic engineering ...

Imaging methods to capture the beating and developing heart inside embryonic animal models such as the zebrafish are a key component for the study of fundamental biological processes such as cardiac birth defects or tissue regeneration. However, live heart ...

Stochastic optimization is a popular modeling paradigm for decision-making under uncertainty and has a wide spectrum of applications in management science, economics and engineering. However, the stochastic optimization models one faces in practice are int ...

The distribution network restoration problem is by nature a mixed integer and non-linear optimization problem due to the switching decisions and Optimal Power Flow (OPF) constraints, respectively. The link between these two parts involves logical implicati ...

The objective of this thesis is to develop a general methodology to incorporate a disaggregate demand representation in supply-oriented optimization problems that allows to capture the interplay between the behavior of individuals and the decisions to be o ...

This research presents a mathematical formulation for optimizing integration of complex industrial systems from the level of unit operations to processes, entire plants, and finally to considering industrial symbiosis opportunities between plants. The fram ...

This study proposes a general framework for topology-finding or topology optimization of tensegrity structures. The existing topology-finding formulation of tensegrity structures based on mixed-integer linear programming (MILP) was improved and transformed ...

What Players do with the Ball: A Physically Constrained Interaction Modeling

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Learning to Remove Cuts in Integer Linear Programming

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

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

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

Quantitative Methods for Omnichannel Decision-Making

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

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

Assortment optimization using an attraction model in an omnichannel environment

Potential of electric mobility as service to the grid in renewable energy hubs

Computational tool for stock-constrained design of structures

Integrating advanced discrete choice models in mixed integer linear optimization

Data reduction for mixed integer linear programming in complex energy systems

Vessel scheduling with pilotage and tugging considerations

Constraint-based metabolic control analysis for rational strain engineering

Computational methods for live heart imaging with speed-constrained microscopes

Scalable Stochastic Optimization: Scenario Reduction with Guarantees

A Novel Decomposition Solution Approach for the Restoration Problem in Distribution Networks

A general framework for the integration of complex choice models into mixed integer optimization

A Mixed-Integer Linear Programming Formulation for Optimizing Multi-Scale Material and Energy Integration

Topology-Finding of Tensegrity Structures Considering Global Stability Condition