Johannes Varga | AC Group | TU Wien

Annoyance Modeling in Cooperative Personnel Scheduling

Thu, 01 Jan 2026 00:00:00 +0000

Learning to Predict User Replies in Interactive Job Scheduling

Thu, 01 Jan 2026 00:00:00 +0000

Selecting User Queries in Interactive Job Scheduling

Wed, 01 Jan 2025 00:00:00 +0000

Tackling the Alpha-Domination Problem Heuristically

Wed, 01 Jan 2025 00:00:00 +0000

Cooperative Personnel Scheduling

Mon, 01 Jan 2024 00:00:00 +0000

a joined research project from the Algorithms and Complexity Group, TU Wien, Austria, and Honda Research Institute, Germany

Project Team

Topic

In classical personnel scheduling, the employees of a company are assigned their schedules, which determine at which times they work to fulfill some kind of demand. Our setting is slightly different. Each employee also referred to as a user, has some jobs to complete that need a specific resource. Only a limited amount of resources is available and only one job can use a resource at a time. Each job has to be assigned to a resource and a timespan in which the job is carried out. Furthermore, users will have preferences on when their jobs should be executed. These preferences have to be collected in some way. One possibility would be to let the employees specify their full preferences in the beginning. But this is tedious for the employees, error-prone and only allows for preferences that were explicitly considered when designing the algorithm.

In this project, we will develop and investigate a framework that learns these preferences over time through a limited amount of user interactions. The framework aims to construct schedules that respect employees’ preferences and are feasible with the given restrictions. While constructing the schedules it is allowed to ask the employees a limited number of questions regarding their preferences. The responses to these questions are used to model the employees’ preferences. The framework may also consider fairness, e.g. by balancing the number of user interactions among the employees. Research questions to answer include which algorithms work well for the occurring problems, how to model the employees’ preferences, and which kind of user interaction gives sufficient information on the preferences, without overwhelming the employees.

Mixed Integer Linear Programming Based Large Neighborhood Search Approaches for the Directed Feedback Vertex Set Problem

Mon, 01 Jan 2024 00:00:00 +0000

Scheduling Jobs Using Queries to Interactively Learn Human Availability Times

Mon, 01 Jan 2024 00:00:00 +0000

Speeding up Logic-Based Benders Decomposition by Strengthening Cuts with Graph Neural Networks

Mon, 01 Jan 2024 00:00:00 +0000

An Evolutionary Approach for Scheduling a Fleet of Shared Electric Vehicles

Sun, 01 Jan 2023 00:00:00 +0000

Interactive Job Scheduling with Partially Known Personnel Availabilities

Sun, 01 Jan 2023 00:00:00 +0000

Large Neighborhood Search for Electric Vehicle Fleet Scheduling

Sun, 01 Jan 2023 00:00:00 +0000

Computational Methods for Scheduling the Charging and Assignment of an On-Site Shared Electric Vehicle Fleet

Sat, 01 Jan 2022 00:00:00 +0000

Computational Methods for Fleet Scheduling in E-Mobility

Sun, 01 Aug 2021 00:00:00 +0000