Assignments (theses)

Researchers of DMMP work in several research areas with applications in different fields, like health care, traffic, energy, ICT, games and auctions, logistics and timetabling. The overview of previously completed theses gives an indication of what kind of topics for a final assignment are possible. We collaborate with different external partners outside of the UT for internships and final assignments, and to name only a few, that could be DAT.mobility, ORTEC, Thales, NS, CQM, and many more. Also foreign Universities are an option. The list below in therefore indicative, and shows a few of the open problems to work on.


List of Potential MSc Topics

The following list of potential MSc topics is always under construction and will be updated regularly. If you are interested in assignments for an internship or a master's thesis, please contact any member of the group. At the end of the page, a list of completed master's theses can be found.


  • Mathematical Optimization in Smart Energy Grids

    MSc Thesis

    Mathematical optimization plays a large role in the coordination of smart residential energy systems. In these systems, on the one hand, there is an increased infeed of renewable energy (solar, wind). On the other hand, the rising number of electric vehicles, heat pumps, and other “smart devices” leads to an increase of the residential energy demand. This increase is so extreme that it can cause blackouts if not managed properly.

    In order to reduce the risk of blackouts, we can reduce peak consumption or production by exploiting the flexibility of smart devices. This is where mathematical optimization comes into play: one can formulate the problem of peak minimization as a mathematical program that can be solved using either standard solvers or, preferably, efficient tailored algorithms.

    Within this broad topic, there are several possibilities for MSc theses. Following are three examples of research projects:

    • In our optimization models, we make many assumptions on the properties of devices in order to obtain efficient (i.e., polynomial-time solvable or convex) models. Examples of this are continuous charging behavior, minimal losses, and perfect state-of-charge measurements. To what extend can these assumptions be relaxed while maintaining the efficiency?
    • The (electricity) distribution grid has a hierarchical network structure with different levels. At the bottom of the hierarchy are consumption devices and local energy production devices (e.g., solar panels), whereas higher in the hierarchy are larger grid assets such as transformers. Due to this level structure, peak reduction on all levels is required in order to maintain a proper grid operation. When only two levels are considered, this can be done relatively efficiently. However, as soon as more levels are included, the efficiency decreases drastically due to the increased dimensionality. How can we increase the scalability of peak reduction strategies applied to multiple network levels?
    • One approach to tackle peak consumption or production is by introducing a clever market design. This market structure should be such that everyone is incentivized to participate in reducing the peaks. Existing literature makes extensive use of tools from the area of (Algorithmic) Game Theory. Up to now these approaches differ in many aspects, such as the variety of smart device types, their stability, and their running time. Is there a way to combine the advantages of these approaches or generalize the setting even further (for instance, include uncertainty)?

    For more information, please contact Johann Hurink.

  • Hyperball Algorithms for Conductance

    MSc Thesis

    The hyperball algorithm, based on probabilistic counters, turned out extremely effective and efficient in computing graph distances in gigantic networks, such as Facebook. In this project we will investigate what other important characteristics of networks can be estimated using this powerful method.

    In particular, we focus on the important problem of minimizing conductance: a measure for how well-connected a group of vertices is to the rest of the network. Conductance has many important applications: it gives information on how fast a rumor spreads through a network and it can help in finding ‘communities’, sets of densely connected vertices within a graph. These communities usually have low conductance, and finding good communities then translates to finding sets of low conductance.

    However, finding a set of minimum conductance in a graph is computationally intractable. We will investigate whether we can efficiently find good candidates for sets of minimal conductance using hyperball-type algorithms.

    For more information please contact Clara Stegehuis

  • Algorithms to Run Out Table Cooling in Steel Production (Tata Steel)

    Internship & MSc Thesis

    In a Hot Strip Mill thick steel slabs are hot rolled out to long strips having a thickness range of 2 to 25 mm. After hot rolling the strip needs to be cooled down on the runout Table (ROT) from about 900°C to about 500°C or lower after which the strip is coiled. The new market developments in hot rolled products are mainly in the advanced high-strength steels. These products require a precise and highly flexible control of the cooling path on the runout table. Not only the final temperature (coiling temperature) , but also the cooling rates and intermediate temperatures are important for achieving the right mechanical properties of the steel.

    Before a steel strip enters the ROT, there is limited time available for the controller to determine the optimum setup . As there are many variables involved (the settings of each individual bank, material properties, velocity) of which some variables are discrete (e.g. the valve settings: 0%, 70% or 100% open) it is very complex to find the minimum of the objective function within the limited available time: we have about 6 seconds to find the optimum out of  possible control settings. There are various algorithms available, however, many of them are not suitable to find the global minimum (they might find a local minimum as optimum) and/or are not fast enough to be useful. To find a suitable solution, the method must be able to solve a non-convex (having both local minima and a global minimum), non-linear, and discrete problem.

    This is a project with R&D at Tata Steel (The Netherlands. For more details and a more detailed problem desciption, please contact Johann Hurink or Marc Uetz.

  • The Price of Stability for Matroid Congestion Games

    MSc Thesis

    Congestion games are a fundamental model in optimization and game theory, with applications e.g. in traffic routing. The price of stability is a game theoretic concept that relates the quality of the best Nash equilibrium to that of an optimal solution. It is the "smaller brother" of the well known price of anarchy as defined by Koutsoupias and Papadimitriou in 2001, and has been first defined by Anshelevich et al. in 2004. The basic question that is asked here is if and how the combinatorial structure of the strategy spaces of players  influences the quality of the possible equilibria. In that respect, a recent progress was made for uniform matroids and the price of anarchy, which equals approximately 1.35188. The conjecture is that the price of stability for that (and maybe even for more general models) equals 4/3. The proof of this conjecture is the topic of this project. Background literature is a paper by de Jong, Klimm and Uetz on "Efficiency of Equilibria of Uniform Matroid Congestion Games" as well as the more recent paper "The asymptotic price of anarchy for k-uniform congestion games " by de Jong, Kern, Steenhuisen and Uetz. Both papers are available upon request.

    For further questions, contact Jasper de Jong or Marc Uetz.

  • Equilibria for Set Packing Games

    MSc Thesis 

    In a recent paper (de Jong and Uetz, https://arxiv.org/abs/1709.10289) we have analyzed the quality of several types of equilibria for so-called set packing and throughput scheduling games. In that model, players subsequently select items to maximize the total value of the selected items, yet each player is restricted in the feasible subsets she can choose. The results are bounds on the quality of Nash and other game theoretic equilibria. 

    One of the distinguishing features of that model is that no item can be chosen by more than one player. That is a natural assumption in sequential games, but appears somewhat artificial when considering single-shot games. 

    The question that is to be analyzed in this MSc project is what happens when that assumption is relaxed? First, what type of models adequately model the situation that several players choose one and the same item? And what are the consequences for the resulting equilibria? What is the price of anarchy for pure and mixed Nash equilibria for such a model?

    For more information, please contact Marc Uetz.

  • Sequential Congestion Games and the Price of Anarchy

    MSc Thesis

    In a series of recent publications, several researchers have analyzed sequential games and subgame perfect equilibria in order to circumvent the sometimes bad quality of Nash equilibria. Specifically, de Jong and Uetz (2015) have done that for congestion games with two or three players, showing that the sequential price of anarchy equals 1.5 and 1039/488, respectively. Subsequently, Correa, de Jong, de Keijzer and Uetz (2016) have considered network routing games and showed that -surprisingly- the sequential price of anarchy for games with n players can even be unbounded (while the price of anarchy is only 2.5). All these results are for pure strategy Nash and subgame perfect equilibria.  One of the open questions is what happens if we consider mixed strategies, or settings in which the demand of a player is splittable. As a starting point, one can consider games with two or three players... The underlying research papers are available upon request.

    For further information, contact Jasper de Jong or Marc Uetz.

  • Incentives in Smart Energy Grids

    MSc Thesis

    In the future electricity grid with high penetrations of renewable energy and electric vehicles, we may risk grid overloading and possibly even blackouts. By providing incentives to producers and consumers of electricity, they may change their behaviour such that these problems are prevented.

    A complicating factor is that overloading depends on the total loads in the network in a non-linear way. The main task for this assignment is to study and design suitable price functions or mechanism using game theory.

    We would like to know if there is an incentive scheme that gives an efficient Nash equilibrium under some realistic assumptions.

    This thesis will be jointly supervised by Alexander Skopalik (MOR) and Marco Gerads (CAES)

  • Tracking objects with drones

    MSc Thesis

    Swarms of drones are often used to track targets. Examples range from tracking criminals in cars by the police to tracking sports players to create live footage. Drones can track these objects easily without creating disturbance, as they can move in space.

    To track an object, multiple drones measure their distance to the object, and then together calculate the position of the object. Drones know their own position through GPS measurements. However, these GPS measurements may not be completely accurate, so that drones only know their position with some error. When they position their distance to the target, this means that the position of the target also becomes more uncertain. Based on this uncertain information, the drones have to decide where to move to keep the object in sight. The drones only have a limited angle of sight, and therefore a wrong decision can cause the drones to lose the target.

    So where should we deploy the drones to create a robust strategy that minimizes the probability to lose the target? And if we lose the target, can we come up with a strategy to find it back? In this assignment you will take the probability distribution of the drone locations and their errors into account to determine the optimal strategy to track their target.

    This project will be jointly supervised by Clara Stegehuis (MOR) and Anastasia Lavrenko from Electrical Engineering.

    For more information about this final project, please contact Clara Stegehuis.

  • Designing a Scheduling Model for Autonomous Behaviour of a Social Robot

    Social robots have been used in a number of fields. The UT has had projects that studied the use of these robots in fields like care / cure (ProSPEro, DeEnigma), education (EASEL), police work (R3D3) and even art (Kunst- en Techniekwerk). Across the world, similar projects have carried out studies with available platforms in even more domains, but overall performance remains unsatisfactory because interaction is not fluent and responsive enough to maintain long term appeal. For example, the PRoSPEro project found that care workers who are introduced to working with robots start out having high expectations, after a while report disenchantment with the very limited repertoire of tasks and behaviours that it supports. This leads to the robots not being used so much in the longer term. To improve this situation, social robots that interact with (groups of) people must be expressive in a responsive way.

    One of the challenges that needs to be addressed when designing such robots (we believe) is of an algorithmic nature. A expressive social robot needs to show a mix of active, reactive and reflexive behaviour. However, those behaviours will be in constant conflict with each other, as some tasks cannot be performed in parallel. For instance, a robot cannot look at two different people at the same time and trying to do so might result in a robot that is cross-eyed. Thus, an algorithm should choose in real time if the robot first looks at one person and then at the other or, perhaps, that it only looks at one and ignores the task of looking at the other.

    During this project, you are expected to develop a model that provides a good basis for an algorithm to make scheduling decisions of behavioural tasks of a robot. Subsequently (and likely in parallel), you develop and analyse (an) algorithm(s) that can make these decisions in an online fashion. Ideally, you will implement your algorithm(s) to test on a real robot.

    For this project you should have followed the course Scheduling and you should have an affinity for computer programming.

    The project will be carried out under supervision of Ruben Hoeksma and Edwin Dertien from the Robotics and Mechatronics group (Electrical Engineering).

    For more information please contact Ruben Hoeksma.

  • Recognition of Combinatorial Matrices

    The ultimate goal of topics in this area is the extension of the software library CMR (Combinatorial Matrix Recognition) that contains efficient implementations of recognition algorithms for several classes of matrices. Final projects can involve the following things:

    • Experimental implementation of recognition algorithms (graph or matroid theory, Python programming).
    • Study of recognition problems, (graph or matroid theory, algorithms).

    For those with programming experience in C or C++ there is another option possible:

    • Implementation of algorithms for the CMR library.

    If you find one or more of these topics interesting, please contact Matthias Walter.

  • Mixed-Integer Optimization

    There are various topics available in the broad area of mixed-integer programming (MIP). There are topics about general-purpose MIP, but also those related to concrete applications such as:

    • Production scheduling (machine scheduling)
    • Network design (transportation)
    • Physics (Low Auto Correlation Binary Sequences, ground state of Bernasconi model)
    • Cryptanalysis

    Besides concrete application, foundational topics are also available:

    • Quadratic variants of combinatorial optimization problems
    • Binary polynomial optimization (products of binary variables)

    Irrespective of the potential application, there are different sorts of research that can be carried out:

    • Modeling a problem via MIP forms the basis, but alone is not considered a sufficient contribution for a final project.
    • Find new inequalities to strengthen a formulation (often requires to run code on a console to find these).
    • Prove facetness of inequalities.
    • Develop separation (=row-generation) algorithms.
    • Prove perfection of a formulation (often for a subproblem or relaxation).
    • Evaluate bound improvement computationally (requires Python).

    For those with programming experience in C or C++ there are even more directions possible:

    • Integrate new inequalities in a state-of-the-art MIP solver.
    • Implement decomposition approaches such as Benders' or Dantzig-Wolfe decomposition.

    If you find one or more of these topics interesting, please contact Matthias Walter.

  • Efficient local search heuristics for the TSP

    The traveling salesperson problem (TSP) is a classical NP-hard optimization problem. The task is to find a Hamilton cycle (tour) of minimum length through an edge-weighted graph. TSP has a huge variety of applications and even serves as arguably the most popular benchmark problem to try out techniques in optimization.

    A very popular heuristic to hopefully find close-to-optimal solutions quickly is a simple local search heuristic called k-opt: Given a tour, remove k edges and replace them with k edges such that the result is again a tour, if this shortens the total tour length.

    While in particular 2-opt performs very well in practice, both in terms of quality and in terms of efficiency, it is extremely slow in the worst case. Only recently, efficient restricted variants have been analyzed more closely.

    The goals of this thesis is to adapt and analyze efficient variants of k-opt for the asymmetric TSP and the Euclidean TSP.

    If you are interested, please contact Bodo Manthey.

Completed MSc Theses and Internships

Name

Title

Company

Supervision

Finished

Serge Johanns

High Frequency Trading in Cryptocurrency Options using the Black- Sholes Model

Masternode.one

Alexander Skopalik

2024

Wouter
Doedens

Photovoltaic Power Forecasting

El Niño

Alexander Skopalik

2023

Cas Sitvast

A 3-stage formulation for solving single modular capacitated network design problems


Matthias Walter

2023

Hugo Hof

An implementable Three-in-a-Tree algorithm to accelerate Perfect Graph detection


Matthias Walter

2023

Marnix C. Vos

Equilibria in the Two-Stage Facility Location Game With Unsplittable Clients


Alexander Skopalik, Marc Uetz

2023

Anne Meulenkamp

A 3-stage approach to the berth allocation and quay crane specific problem in container terminals using cutting planes

Cofano

Matthias Walter

2023

Gavin Speek

A method to detect contextual outliers in mobility behaviour

Mobi.dot

Marc Uetz

2023

David van der Linden

Performance Testing of the Steepest Edge and Devex Pricers through hot starting with Objective Perturbations

ZIB

Matthias Walter

2023

Reinout Wijfjes

Aggregation of Strategic Transport Model Systems

DAT.mobility

Alexander Skopalik

2023

Jorn de Jong

Smart scheduling algorithm for an Energy Storage System

El Niño

Matthias Walter

2023

Cas Sitvast

Case Study traffic flow and speed prediction in the traffic network of Groningen

Goudappel & Coffeng

Marc Uetz

2023

Boyue Lin

Almost Core Allocations on Minimum Cost Spanning Tree Games

joint with NPU

Marc Uetz, Matthias Walter

2022

Matthew Maat

Instances with exponential running time for strategy iteration


Georg Loho

2022

Jop Zwienenberg

A Markovian approach to mobile user classification with semantic location data in mobility chains

Mobi.dot

Marc Uetz, Maria Vlasiou

2022

Bozhidar Petrov

Methods for predicting changes in detailed traffic assignments

DAT.mobility

Clara Stegehuis

2022

Anne Meulenkamp

The berth allocation problem

Cofano

Matthias Walter

2022

Saskia Bleyenberg

The Price of Anarchy for Matching Congestion Games


Alexander Skopalik, Marc Uetz

2022

Hugo Hof

Heuristics for a Branch-and-price algorithm for the Rolling Stock Circulation Problem

NS

Matthias Walter

2022

Rutger Mauritz

Planning in Supply Networks Using Aggregated Resource Feasibility

Togetr B.V.

Antonios Antoniadis and Marc Uetz

2022

Puck te Rietmole

Sampling-based Stochastic Single-machine Scheduling

UU

Marc Uetz

2022

Janet Visser

A data driven approach for the modelling of vans

DAT.mobility

Matthias Walter

2022

Reinout Wijfjes

Recognition and Exploitation of Single-Machine Scheduling Subproblems in Mixed Integer Programs


Marc Uetz, Matthias Walter

2022

Feline Lindeboom

Online Scheduling with Rejection

UvA

Ruben Hoeksma, Marc Uetz

2022

Matthew Maat

Value Iteration Algorithms for the STAQ Squeezing Traffic Model

DAT.mobility

Georg Loho, Marc Uetz

2021

Jop Zwienenberg

A probabilistic extension to a rule-based method for activity recognition in mobility chains

mobi.dot

Marc Uetz

2021

Yanna Kraakman

The Price of Anarchy of Symmetric and Semi-Symmetric Uniform Congestion Games


Marc Uetz

2021

Rolf van der Hulst

A branch-price-and-cut algorithm for graph coloring


Matthias Walter

2021

Kitty de Smit

Odd-Cycle Separation for Set Cover


Matthias Walter

2021

Joran van den Bosse

Computing the Sequential Price of Anarchy of Affine Congestion Games Using Linear Programming Techniques


Marc Uetz, Matthias Walter

2021

Wouter Fokkema

The Rectangle Covering Bound on the Extension Complexity of Small Cut Polytopes


Matthias Walter

2021

Hilliane Buist

Online travel mode detection on a smartphone

mobi.dot

Marc Uetz

2020

Rolf van der Hulst

Input Reduction for Junction Modelling in Static Traffic Assignment using Random Forests

DAT.Mobility

Matthias Walter

2020

Lotte Gerards

Extending Static Traffic Assignment with Queuing to a Semi-dynamic Model

DAT.Mobility

Matthias Walter

2020

Tim van Genderen

Solving the trip based transport model using iterative optimization algorithms


DAT.Mobility

Alexander Skopalik, Matthias Walter

2020

Marije Siemann

A polyhedral study of the Travelling Tournament Problem


Matthias Walter

2020

Reinier de Zeeuw

Routing and Guidance for Airplane Taxiing

Saab Technologies

Marc Uetz

2020

Tim van Genderen

Development of a Tour Based Gravity Model

DAT.Mobility

Alexander Skopalik, Matthias Walter

2020

Hilliane Buist

MIP model to compute an optimal curing schedule for Apollo Vredestein B.V.

Apollo Vredestein

Marc Uetz, Matthias Walter

2020

Jacqueline Zijdenbosch

A two-step optimization approach for engagement scheduling

Thales

Marc Uetz

2019

Joren Kreuzberg

Revenue maximizing assignment of products within a physical store layout by Integer Linear Programming

IG&H Consulting

Marc Uetz

2019

Eline van Hove

Train routing at the Shunt Yard: a Disjoint Paths approach

NS

Marc Uetz

2019

Jacqueline Zijdenbosch

Optimizing Group Compositions in Daycare Facilities

Columbus Junior

Alexander Skopalik, Marc Uetz

2019

Eveline Koster

Determining Good Configurations and a New Strategy for Multi-Process Optimization within ORTEC

ORTEC

Marc Uetz

2019

Jan-Tino Brethouwer

The quality of equilibria in generalized market sharing games


Jasper de Jong, Alexander Skopalik, Marc Uetz

2018


Mark Pots

Gravity model parameter calibration for large scale strategic transport models

Goudappel Coffeng

Peter Dickinson

2018

Sander Visser

Probabilistic analysis of optimization problems in random shortest path metrics applied to Erdős–Rényi random graphs


Bodo Manthey

2018

Bernike Rijksen

Matrix Estimation with STAQ

DAT.Mobility

Georg Still

2018

Ingrid Maas

Minimising road infrastructure maintenance costs by managing the traffic

DAT.Mobility


Peter Dickinson, Marc Uetz

2018

Eline van Hove

The Linear Threshold Rank as Centrality Measure in Social Networks

U Politècnica de Catalunya

Marc Uetz

2018

Joren Kreuzberg

Online-offline solution comparison for the Vehicle Incident Dispatching Problem

EY Advisory

Marc Uetz

2018

Berend Steenhuisen

Asymptotic price of anarchy for affine, symmetric, k-uniform congestion games


Walter Kern, Marc Uetz

2017

Eloy Stoppels

Predicting race results using artificial neural networks

Mylaps

Marc Uetz

2017

Jaap Slootbeek

Average-Case Analysis of the 2-opt Heuristic for the TSP


Bodo Manthey

2017

Jelle Neeft

Multimodal Map Matching with smartphone data: a shortest path approach

Mobidot.com

Marc Uetz

2017

Matthijs Tijink

Perturbation resilience for the facility location problem


Bodo Manthey

2017

Joram Span

Dynamic pricing for camping and bungalow parks: integer linear programming for revenue maximization

Stratech

Marc Uetz

2017

Kiril Delianov Kolev

Sequential price of anarchy for atomic congestion games with limited number of players


Jasper de Jong, Marc Uetz

2016

Loes Knoben

Optimizing the moment of customer delivery in ORTEC Inventory Routing

ORTEC

Marc Uetz

2016

Femia van Stiphout

Approximating the Flow-Based Transport Capacity Constraints for the Day-Ahead Power Market

Eneco

Johann Hurink, Marc Uetz

2016

Stefan Klootwijk

Probabilistic Analysis of Facility Location on Random Shortest Path Metrics


Bodo Manthey

2016

Victor Reijnders

Probabilistic analysis of highly connected random geometric graphs


Bodo Manthey

2016

Dorien Meijer-Cluwen

Dynamic Room Allocation - Adaptive planning of teaching facilities at the University of Twente

CES U Twente

Marc Uetz

2016

Selmar van der Veen

Workforce scheduling algorithms at Grolsch Brewery Enschede

Grolsch

Marc Uetz

2016

Victor Reijnders

A spatial optimisation model for fuel management to break the connectivity of high-risk regions while maintaining habitat quality

U Melbourne

Marc Uetz

2016

Ingrid Maas

Computing Revenue Maximizing Auctions in the Presence of Transaction Fees

U Warwick

Marc Uetz

2016

Sijmen de Bruin

Data association for multiple extended target tracking

Thales

Walter Kern, Georg Still

2015

Oedsen van der Kooi

Traffic Assignment with Junction Modeling in TAPAS

DAT.Mobility


2015

Femia van Stiphout

The Firefighter Problem on Cubic Graphs

UPC Barcelona

Marc Uetz

2015

Loes Knoben

The S-Bahn Challenge in Berlin

ZIB Berlin

Marc Uetz

2015

Anton Dijkstra

Optimizing the material flow at Bosch: supplying the Deventer plant with materials for making heating boilers

Bosch


2014

Peter Vermaas

Increasing tracking performance by improving waveform design

Thales


2014

Leon Schimmel

Model gebaseerde regelaar voor riolering

Witteveen+Bos


2014

Ha Nguyen

Fast and Scalable Algorithm For Sequencing Problems with Private Information


Marc Uetz, Ruben Hoeksma

2014

Marten Waanders

Approximation Algorithms for Connected Graph Factor Problems



2014

Enno Boersma

VOC soil contamination in urban area: an approach for determining spatial distributions and behaviour in time

Witteveen+Bos


2013

Maarten Vinke

An approximate dynamic programming approach to the micro-CHP scheduling problem



2012

Jessica Groenhuis

Bus Network Design

Omnitrans

Marc Uetz

2012

Ferry Kristanto

An allocation approach of sponsored search auctions



2012

Erik van Holland

Contributions to bin packing games



2012

Mathijs ter Braak

A hyperheuristic for generating timetables in the XHSTT format



2012

Roelof Spijker

Generic scheduling in radar systems

Thales


2012

Sytse Bisschop

Logistics behind Wheel Rail Conditioning

Structon Rail


2012

Heleen Muijlwijk

Static traffic Assignment with Junction Modelling

Omnitrans International B

Marc Uetz

2012

Arjan Feenstra

Optimale seinplaatsingen: een branch-and-bound algoritme voor de plaatsing van spoorwegseinen

Movares


2012

Bas Joosten

Relaxations of the 3-partition problem

Radboud Universiteit


2011

Maarten Bos

Programming a CNC-machine using ILP




2011

Sophie van Veldhoven

Days off personnel scheduling


Gerhard Post

2011

Matthijs Bijl

Strategisch plannen met BOSS

ORTEC


2011

Mirel Maraha

Efficiënter gebruik van CT-scanners: casus bij Medisch Spectrum Twente

MST


2011

Jasper de Jong

Het ontwerpen van patronen voor polymetrische metselwerken




2011

Tim Broeken

Het simuleren van de business-simulatie FleXnet

KEMA


2011

Jaap Koelewijn

Graph-theoretical aspects of constraint solving in the SST project



2011

Jelle Duives

Mathematical programming approach to multidimensional mechanism design for single machine scheduling



Marc Uetz

2011

Harald Emsbroek

Vloeistoffen in discrete simulatie

Talumis


2011

Léon Klunder

Multiple Target Tracking with Closely Spaced Targets

Thales


2011

Stijn Duyzer

Minimum-Cost Multi-Modal Paths with Arrival Time Constraint

COM

Marc Uetz

2011

Ben Rorije

Calibrating OD-matrices with public transport and mobile phone data

Omnitrans


2011

Arjan van Leeuwen

Static Traffic Assignment with Queuing

Goudappel Coffeng


2011

Arjan Thomas

A generic model for tactical planning problems

ORTEC


2011

Caroline Jagtenberg

On Machine Scheduling with Exponentially Distributed Processing Times

Universiteit Utrecht

Marc Uetz

2010

Ruben Hoeksma

Price of anarchy for machine scheduling games with sum of completion times objective


Marc Uetz

2010

Woutske Hartholt

Beslissingsondersteuning voor het aanpassen van de online OK-planning

Isala


2010

Matthias den Hartog

Shunt planning: an integral approach of matching, parking and routing

NS-Reizigers


2010

Faizan Ahmed

Relations between semidefinite, copositive, semi-infinite and integer programming



2010

Xian Qiu

Bin packing games



2010

Yuan Feng

Modified potential approach to efficient, linear and symmetric values for TU-games



2010

Aleida Braaksma

Integral multidisciplinary rehabilitation treatment planning

AMC


2010

Eric Raesen

A time-based order fill rate model for spare parts

VanderLande


2009

Wendy Stut

Een stochastisch optimalisatie model voor een robuuste dienstregeling: Een nieuwe oplosmethode

NS-Reizigers


2009

Diana van de Weijenberg

Seinplaatsing Spoorwegen

Movares


2009

Anthony Ohazulike

Multi-Objective Road Pricing Problem: A Cooperative and Competitive Bilevel Optimization Approach

Goudappel Coffeng


2009

Kamiel Cornelissen

Algorithmic feature generation for microscale topographies


Marc Uetz

2009

Ties Brands

Optimization of Toll Levels in Networks

Goudappel Coffeng


2008

Anke Rouwette

Suppy Chain Optimization

Unilever


2008

Maarten Schilpzand

New Junction Modelling in Macroscopic Dynamic Traffic Assignment Models

Omnitrans


2008

Dieuwke Vijselaar

Het positioneren van ambulances

Ambulance Oost


2008

Maurice Bosman

Frequency Assignment

Cass Business School


2008

Jan-Maarten Verbree

Lifetime of Mobile Networks

Thales


2007

Matthijs Bomhof

Approximation Algorithms



2007

Gwendy van Schooten


Unilever


2007

Mark van der Spoel

Route planning

Siemens VDO Trading


2006

Ingrid Koens


EMC


2006

Remko Stam

Supply chain of beer boxes

Grolsch


2006

Pim van 't Hof

Graph coloring

University of Klagenfurt


2006

Leendert Kok

Scheduling with spatial resources



2006

Ellen Even

Bemanningsconcepten: een model voor het bepalen van een bemanningsgrootte en samenstelling

TNO-FEL


2006

Marcel van den Brink

Planning of parent-teacher meetings



2006

Casper Middelkamp

Transport of rail carriages to maintenance

NS-Reizigers


2005

Jeroen van Oostrum

Master surgical schedules in hospitals

EMC


2005

Tom Guldemond

Time-constrained project scheduling

ORTEC


2005

Marc Wolbers

Decision Support for compatible routes

Holland Railconsult


2005

Ronal Landman

Creating timetables for Dutch high schools



2005

Jacob Jan Paulus

Online matching on a line



2005

Bert Marchal

Backbone colorings of graphs



2004

Hilbrandt Baarsma

Implementing DSP-algorithms on the Montium architecture

With INF group


2004

Conno Hendriksen

Capacity planning in an engineer-to-order environment

with TBK group


2004

Maarten Kroon

Planning of shift sequences in personnel rosters

ORTEC


2004

Bas Heideveld

Scheduling in a rolling horizon environment

with TBK group


2004

Timo Septer




2004

Bianca Makkink

The power of rolling horizon

Paragon


2004

Ingrid van Riel

Operations research in practice

Tebodin


2004

Inge Ruel

Research for new possibilities within logistics

Essent


2004

Leo van Iersel

Radar cluster algorithms

Thales


2004

Bastiaan ten Broeke

Road network vulnerability

Goudappel Coffeng


2004

Peter de Haan

Timetabling in Dutch secondary schools



2004

Karin Baak

Dropping transport regulations

Centraal Boekhuis


2004