Bachelor Theses in Discrete Optimization
In general, a bachelor thesis is based on a mathematical article that is reviewed and expressed with own words. Frequently, this comes along with small implementation tasks or computational experiments.
The time horizon of a bachelor thesis is six months. Before starting, be sure to read the Handout (opens in new tab) on bachelor theses in discrete optimization. The work is usually registered when the student became acquainted with the topic. For the preparation of the thesis, a TeX template is available in Downloads. Alternatively, you an also use the template of the“Arbeitstechniken” lecture from WS15/16.
Requirements
The successful pass of the course “Introduction to Optimization” is required; in addition, the active participation in an optimization seminar is strongly recommended.
Contact
Prof. Pfetsch , Prof. Disser and staff members of the research group
- A Polynomial Combinatorial Algorithm for Generalized Miniumum Cost Flow
(Prof. Pfetsch)
- Approximation of the rectangular knapsack problem
(Prof. Pfetsch) - Secretary and online matching problems with machine learned advice
(Prof. Pfetsch) - Optimisation of a CubeSat Evaluation Function
(Prof. Pfetsch) - Reachability in choice networks
(Prof. Pfetsch)
- Using the minimum maximum flow degree to approximate the flow coloring problem
(Prof. Pfetsch) - Generalized Roof Duality
(Prof. Pfetsch) - Kombinatorische zweistufige minmax Regel-Probleme unter Unsicherheitsintervallen
(Prof. Pfetsch) - Identifying relative irreducible infeasible subsystems of linear inequality systems
(Prof. Pfetsch) - The sparsest solution of teh union of finite polytopes
(Prof. Pfetsch) - Grady colorings of words
(Prof. Pfetsch)
- The sparest solution of the union of finite polytopes via its nonconvex relaxation
(Prof. Pfetsch) - Latent Space Optimization: Solving Discrete, High-dimensional and Expensive Problems via the Latent Space of Deep Generative Models
(Prof. Pfetsch) - The constraint Reliable Shortest Path Problem in stochastic Time-Dependent Networks
(Prof. Pfetsch) - Multicommodity flows in symmetric digraphs
(Prof. Pfetsch) - The extraction and expansion method for graph coloring
(Prof. Pfetsch) - Locally monotone Boolean and pseudo-Boolean functions
(Prof. Pfetsch) - Das Intervall-Ordnungsproblem
(Prof. Pfetsch) - The Constrained Reliable Shortest Path Problem in Stochastic Time – Dependent Networks
(Prof. Pfetsch)
- Analysis and Test of Algorithms for the Monoid Resource Constrained Shortest Path Problem
(Prof. Pfetsch) - Generative Adversarial Nets
(Prof. Pfetsch) - Algorithm to solve the Steiner tree problem
(Prof. Pfetsch) - Robust regret combinatorial optimization for shortest path problems
(Prof. Pfetsch)
- Solving all-pair shortest path by single-source computations: Theory and Practice
(Prof. Pfetsch) - Online Dial-a-Ride
(Prof. Disser) - Solutions for Knapsack problem with conflict and forcing graphs of bounded clique-width
(Prof. Pfetsch) - Algorithms to solve the Survivable-Network-Design-Problem
(Prof. Pfetsch) - All pairs shortest path algorithm with single-source compution
(Prof. Pfetsch)
- Genetic Algorithms for the Dial-a-Ride Problem
(Prof. Disser) - Solving the rectilinear distance problem
(Prof. Pfetsch) - Scheduling for a processor sharing system with linear slowdown
(Prof. Pfetsch) - Minimum equivalent precedence relation systems
(Prof. Pfetsch) - Optimal ordering of statistically dependent tests
(Prof. Pfetsch) - Hardness of the burning number of a graph
(Prof. Pfetsch) - Exact algorithms for the solution of the grey pattern quadratic assignment problem
(Prof. Pfetsch) - Proof of a O(log2k) bound for the K-Server problem on HST's
(Prof. Disser) - Algorithms for non-linear and stochastic resource constrained shortest paths
(Prof. Pfetsch)
- Containment of Virus Expansion in Graphs
(Prof. Disser) - State of the Art for the List Update Problem
(Prof. Disser) - Shortest Distances on Undirected Graphs
(Prof. Pfetsch) - Blocking Unions of arborescences
(Prof. Pfetsch) - Efficient recovery of block-sparse signals
(Prof. Pfetsch) - Matching Interdiction
(Prof. Pfetsch) - Efficient solutions for weight-balanced partitioning problems
(Prof. Pfetsch) - Approximation algorithms for maximum K-vertex cover
(Prof. Pfetsch) - Machine Learning for Fraud Detection in E-Commerce
(Prof. Pfetsch) - Shortest Paths for Planar Graphs
(Prof. Pfetsch) - Covering problems in edge- and knot-weighted graphs
(Prof. Pfetsch) - On the robust shortest path problems
(Prof. Pfetsch) - An algorithm for solving parametric flow maximization problems
(Prof. Pfetsch) - The K-Server Problem
(Prof. Disser) - Single machine scheduling with supporting tasks
(Prof. Pfetsch) - A testbed for online Dial-a-Ride on the line
(Prof. Disser) - Anchored rectangle and square packings
(Prof. Pfetsch)
- Improving Bounds for Incremental Maximization
(Prof. Disser) - Max Flows in O(nm) Time, or Better
(Prof. Pfetsch) - Routing in Netzwerken mit Kapazitäten
(Prof. Pfetsch) - Belegungsplanung mit ressourcenabhängigen Bearbeitungszeiten
(Prof. Pfetsch) - Polynomielle Approximationsschemata für das budgetierte Matching-Problem und das budgetierte Matroid-Intersektions-Problem
(Prof. Pfetsch) - Polynomieller Netzwerksimplexalgorithmus für Kosten-minimale Flüsse
(Prof. Pfetsch) - Scheduling Unrelated Parallel Machines and Graph Balancing
(Prof. Pfetsch) - Berechnung kürzester Wege auf Flächen
(Prof. Pfetsch)
- Optimale Approximation mit stückweise affinen Modellen
(Prof. Pfetsch) - Gewichts-beschränkte kürzeste Wege Probleme
(Prof. Pfetsch) - Der Seitenflächen-Algorithmus für lineare Optimierungsprobleme
(Prof. Pfetsch) - Compact Flows
(Prof. Pfetsch) - Solving Combinatorial Optimization Problems via Inclusion-Exclusion
(Prof. Pfetsch) - The Stoer-Wagner algorithm for minimum cuts in undirected graphs
(Prof. Pfetsch) - A recognition algorithm for unit interval graphs
(Prof. Pfetsch) - Approximationsalgorithmen für das Scheduling auf parallelen Maschinen
(Prof. Pfetsch) - Differences between maximum degrees and clique numbers in graphs
(Prof. Pfetsch) - Image Segmentation via Minimum Cuts in Planar Graphs
(Prof. Pfetsch)
