See MOR-DMMP

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 Nelly Litvak or Clara Stegehuis

Potential Games for Caching in 5G Networks

MSc Thesis

Future mobile networks, 5G and beyond, will make use of proactive caching in the base stations. This means that based on predicted user behavior, content is placed in base stations before it is actually requested. The advantage is that delivery latencies are reduced, since once a request for content comes it does not need to be fetched from the server. Moreover, it enables load-balancing in the backhaul of the network, updating the content of the caches only if the network load is low. Since storage capacity in a base station is limited we cannot cache all content. At the same time, since most locations are covered by multiple base stations we want to prevent overlap in the cached content between those base stations. The mathematical challenge that arises is to decide which content to cache in which base station.

The resulting optimization problem is not convex and cannot be tackled straightforwardly. In this project you will work on a distributed optimization algorithm that can be interpreted as a potential game played between the base stations in the network. A basic version of such an algorithm has been proposed in the literature, but the underlying theory needs to be further developed. In this project you will develop this theory, with the purpose of providing performance guarantees on the algorithm (convergence rate, quality of solution,…) as well as refinements/improvements on the algorithm itself.

You will be working with algorithmic game theory and in particular with the class of (matroid) congestion games. In such a game we assume that the players behave selfish and are interested to optimize their personal utility only. Game theory predicts that such a behavior leads to an equilibrium solution which has been studied extensively. Interestingly, the distributed algorithm outlined above can be described as a game such that the solution of the algorithms corresponds to an equilibrium of the game. You will apply and refine game theoretic methods to analyze the quality of equilibria and the convergence rate.

Knowledge of 5G and/or caching is not required before starting this project.

Please contact Alexander Skopalik or Jasper Goseling.

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.

Smoothed Analysis of High-Dimensional Optimization Problems

MSc Thesis
For many optimization problems, finding optimal solutions is prohibitive because the problems are NP-hard. This often holds even in the natural case, where the instances of the optimization problem consists of points in the Euclidean plane. In order to still be able to solve these problems, heuristics have been developed in order to find close-to-optimal in reasonable time. While many such heuristics show a remarkable performance in practice, their theoretical performance is poor and fails to explain practical observations.

Smoothed analysis is a relatively new paradigm in the analysis of algorithms that aims at explaining the performance of such heuristics for which there is a gap between theoretical analysis and practical observation.

Recently, Bläser et al. (Smoothed Analysis of Partitioning Algorithms for Euclidean Functionals, Algorithmica, to appear) have developed a framework to analyze so-called partitioning heuristics for optimization problems embedded in the Euclidean plane. The goal of this thesis is to generalize this framework to higher dimensions and to apply it to analyze further heuristics for Euclidean optimization problems.

For more information, please contact Bodo Manthey.

Brouwer vs. Nash

MSc Thesis

In Game Theory we learn that the existence of Nash equlilibria (Nash's Theorem) follows from Brouwer's Fixed Point Theorem. How about the converse? The answer depends on which version of Nash's Theorem we take, but  details must still be clarified. In addition: literature study and overview to see what is known w.r.t. complexity of the two problems (computing fixed points vs. computing Nash equlibria).

Please contact Walter Kern.

Allocations in Simple Games

MSc Thesis

Let N be a set of n=|N| players. A simple game is defined by a partition of the power set of N into two non-empty sets L and W, W the set of winning coalitions, and L the set of losing coalitions, such that L is closed under taking subsets and hence W is closed under taking supersets. Most well-known are weighted voting games, where each player i in N has an associated nonnegative weight p(i) and winning coalitions W are defined by p(W) being at least equal to 1. To check whether a simple game is a weighted voting game, one is led to consider

For weighted voting games, the min max value is less than 1. In general this ratio may be seen as measuring the distance of a simple game to weighted voting games. For general simple games, a conjecture  states that the optimum is at most n/4.

Assignment: Study particular classes of simple games or try to prove (approximately) the conjecture. Please contact Walter Kern.

Matchings meet Matroids

MSc Thesis

Matroid Matching (also known as linear matroid parity) is a generalization of matchings (in nonbipartite graphs) and matroid intersection. Recently, an algorithm to solve the weighted version in polynomial-time was devised for the case of matroids that are derived from a matrix.

There is a straight-forward integer linear optimization formulation for the problem. The recent algorithm shows that solving the integer program is tractable. We are now interested in an LP description of the problem, i.e., an the convex hull of the solution vectors.

The first step of the project is to study (the small amount of) existing literature on this matroid matching polytope. One of the known results is an LP formulation in terms of additional variables if the underlying matroid is of a special type. In this case, the polytope is in fact the projection of some matching polytope. Consequently, the second step of the project is to describe the projection of this matching polytope in the original space, i.e., to project out the auxiliary variables. In a third step, further missing inequalities (for the general case) can be derived with the help of computer programs. Their structure shall be described mathematically.

Knowledge from Optimization Modeling is required.

For more information, please contact Matthias Walter.

Cutting Planes vs. Strong Branching in Mixed-Integer Programming

MSc Thesis

Strong branching is a technique used in mixed integer programming (MIP) solvers. A few iterations of the Simplex method are performed in order to obtain good estimates on the effect of branching on a specific variable.

Another useful technique is the generation of cutting planes, especially for the initial LP relaxation. Some of these cutting planes are obtained by hypothetically branching on a variable. Examples are Chvátal-Gomory cuts, MIR cuts and Lift-and-Project cuts.

The goal of this thesis is to understand how the outcome of strong branching is influenced by cutting planes.

Knowledge of C/C++ is required in order to be able to work with the MIP solver framework SCIP.

For more information, please contact Matthias Walter.

Reverse Strong Branching

MSc Thesis

Strong branching is a technique used in mixed integer programming (MIP) solvers. A few iterations of the Simplex method are performed in order to obtain good estimates on the effect of branching on a specific variable.

A new idea, called reverse strong branching, is quite different, but shall achieve the same goals. The goal of this thesis is to complete the idea, implement it within a state-of-the-art solver, and evaluate performance and quality of the approach.

Knowledge of C/C++ is required in order to be able to work with the MIP solver framework SCIP.

For more information, please contact Matthias Walter.

Computing the Smallest LP for the Maximum Cut Problem

MSc Thesis

One approach in combinatorial optimization is to express an optimization problem as an LP. In the past decade it was (essentially) proved that the smallest LP for solve the maximum cut problem for the complete graph with n nodes requires at least 1.5n inequalities. The best-known upper bound is 2n. This result was achieved by the so-called rectangle covering bound. The goal of this thesis is to compute the exact value of this bound for small n.

To achieve this, a sequence of different mixed-integer programs needs to be solved using a standard solver. Moreover, a suitable enumeration algorithm for inclusion-wise maximal bipartite cliques (in a bipartite auxiliary graph) must be developed and implemented efficiently for which simple programming skills are helpful.

Knowledge from Optimization Modeling is required.

For more information, please contact Matthias Walter.

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)

Deployment of swarms of drones

MSc Thesis

Swarms of drones are often used for public safety and disaster management. For example, drone swarms have recently been used to search for terrorists in a mass shooting in Thailand, or to save Koala’s in Australian forest fires. Drones can accomplish these missions fast, safe, and are able to work in hard-to-reach places.

However, during emergency missions, drones may not be able to communicate due to the hard circumstances. Therefore, the drones have incomplete information on where the other drones are. Furthermore, the connection between drones may change over time as the drones move. So where should the drones be deployed, given these uncertainties? How can we calculate the probability of a loss of connection? And when should the drones return to the charging station?

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

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

Polyhedral Relationships between MaxCut, QUBO, Stable Set and Set Covering

Within this project, we consider the following problems:

  1. MaxCut: Given a graph, find a maximum weight cut.
  2. QUBO: Minimize a quadratic polynomial over binary variables (without other constraints)
  3. Stable Set: Given a graph, find a maximum weight independent set.
  4. Set Cover: Given a family of subsets of a ground set, select a maximum weight subset of them such that each element of the ground set is covered.

The first three problem all can be reduced to each other and also reduced to the fourth problem. The goal of the thesis is to investigate how well this works for the LP relaxations of standard IP formulation and for classes of cutting planes.

Knowledge from Optimization Modeling is required.

For more information, please contact Matthias Walter.

Robust Optimization for Smart Deployment of post-5G/6G Communication

MSc Thesis

This is a joint project with Computer Science and Electrical Engineering. Here is the project description.

For more information, please contact Matthias Walter.

Completed MSc Theses and Internships

Name

Title

Company

Supervision

Finished

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