Hyper-Heuristic Design for Unrelated Machines Environment with Auxiliary Resources Main information Project ID: UIP-2025-02-8039 SummaryThe scheduling problem in an unrelated machines environment is the most general variant of scheduling problems in which a job must be executed on a single machine. As such, it is applicable to problems such as multiprocessor scheduling, semiconductor manufacturing, and photolithography workshops. This project will focus on the scheduling problem in an unrelated machines environment with auxiliary resources. These auxiliary resources are required for job execution and include human work or materials necessary for executing jobs. One approach to solving this problem includes problem-specific heuristics, among which dispatching rules are the most common. Dispatching rules are a fast and simple heuristic approach applicable in dynamic environments where not all system information is known in advance. Dispatching rules are widely used since real-world problems often occur in dynamic conditions. However, designing these rules is a challenging task that typically requires problem-specific knowledge, making it necessary to create specific rules for each optimization criterion and problem variant.This project aims to develop a hyper-heuristic method capable of generating dispatching rules for the scheduling problem in an unrelated machines environment with auxiliary resources. Different variants of this problem will be identified as part of the project, and guidelines will be provided on applying the proposed hyper-heuristic method to each. Additionally, the proposed hyper-heuristic method will be adapted to develop dispatching rules that are aware of their dynamic environment and capable of optimizing multiple criteria simultaneously. The project will also examine different methods for further improving the performance of the developed dispatching rules. Finally, additional adaptations of the developed heuristic will be made to ensure its applicability to scheduling problems in photolithography workshops. Project duration: 01.04.2026. – 31.03.2031. Publications Journal publications M. Đurasević, M. Đumić, F.J. Gil-Gala, Automated design of relocation rules for the dynamic container relocation problem, Complex & Intelligent Systems (2026) Conferences publications J. Sabljo, M. Đumić, M. Đurasević, Evolving Dispatching Rules for the Unrelated Parallel Machines Scheduling Problem with Precedence and Resource Constraints with Genetic Programming, GECCO ’26: Proceedings of the Genetic and Evolutionary Computation Conference, San Jose, Costa Rica, 2026, 817-825 J. Sabljo, M. Đumić, M. Đurasević, Analysis of Training Models for Evolving Heuristics in the Unrelated Parallel Machines Scheduling Problem with Additional Resources, 49th ICT and Electronics Convention MIPRO 2026, Opatija, 2026 Conferences J. Sabljo and M. Đumić, GECCO ’26, San Jose, Costa Rica, July 13 – 17, 2026 J. Sabljo, 49th ICT and Electronics Convention MIPRO 2026, Opatija, 2026 M. Đumić, 21st International Conference on Operational Research September 23-25, 2026, Brela Croatia Training and Mobility J. Sabljo, SPECIES Summer School, August 26-31, 2026, Moraira, Spain J. Sabljo, SIGEVO Summer School, GECCO 2026, July 10-12, 2026, San Jose, Costa Rica News Fully supported by Main informationPublicationsConferencesDisseminationNews Project team members Rebeka Čorić Mateja Đumić Josipa Sabljo