Hyper-Heuristic Design for Unrelated Machines Environment with Auxiliary Resources

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Project ID: IP-2025-02-8039

Summary

The 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.

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