Short-Term Scientific Mission

Towards Deriving Incremental Optimization Problems from Batch Specifications of ROAs

Main theme: Problem Modelling and User Experience
Grantee: Maximilian Kratz, Technische Universitat Darmstadt, Darmstadt, Germany
Host: Steffen Zschaler, King's College London, London, United Kingdom

Start date: 2025-09-08
End date: 2025-09-19
Awarded: 2025-06-05

Description

The proposed STSM aims to explore how to systematically derive incremental optimization problems from batch-based specifications in the context of Random Optimization Algorithms (ROAs). Using two case studies (teaching assistant allocation and nurse scheduling), the project investigates the development of a (semi-)automated method to adapt solutions when small changes to the initially specified problem (e.g., unavailability of certain resources) occur. By combining model-driven software engineering techniques with the ROAR-NET API, the mission seeks to prototype and formalize an approach for incrementalization. The outcomes are expected to support the derivation of incremental versions in the two exemplary batch-based problem domains, with potential generalization to other domains.