Optimalizační metaheuristiky patří k velice efektivním metodám pro řešení velké třídy inženýrských úloh. Příkladem takových úloh mohou být úlohy kombinatorické optimalizace jako např. job-shop scheduling, kvadratický přiřazovací problém, či obecný problém splnitelnosti. Limitujícím faktorem pro efektivní využití metaheuristik je vysoká výpočetní náročnost. Cílem předloženého projektu je vytvořit a ověřit akcelerované implementace pokročilých algoritmů CMA-ES, HC12 a distribuovaných GA.

FIT/FSI-J-22-7980

Czech

Chlebík Jakub, Ing. - principal person responsible
Dobrovský Ladislav, Ing., Ph.D. - fellow researcher
Holoubek Tomáš, Ing. - fellow researcher
Jaroš Jiří, doc. Ing., Ph.D. - fellow researcher
Jaroš Marta, Ing., Ph.D. - fellow researcher
Matoušek Radomil, prof. Ing., Ph.D. - fellow researcher

Department of Computer Systems
- responsible department (16.2.2023 - not assigned)
Faculty of Information Technology
- responsible department (8.2.2022 - 16.2.2023)
Department of Computer Systems
- internal (1.1.2022 - 31.12.2022)
Faculty of Mechanical Engineering
- internal (1.1.2022 - 31.12.2022)
Institute of Automation and Computer Science
- internal (1.1.2022 - 31.12.2022)
Faculty of Information Technology
- beneficiary (1.1.2022 - 31.12.2022)

CHLEBÍK, J.; JAROŠ, J. Evolutionary NAS for Topology of an Acoustic Propagation Predictor. Soláň: 2022. p. 0-0.
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JAROŠ, M.; JAROŠ, J. Optimization of Execution Parameters of Moldable Ultrasound Workflows Under Incomplete Performance Data. In Job Scheduling Strategies for Parallel Processing. Lecture Notes in Computer Science, LNCS 13592. Virtual Event: Springer Nature Switzerland AG, 2023. p. 152-171. ISBN: 978-3-031-22697-7.
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JAROŠ, M.; TREEBY, B.; JAROŠ, J. k-Plan: From the Hospital to the Cluster and Back. Ostrava: 2022. p. 0-0.
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JAROŠ, M.; JAROŠ, J. k-Dispatch's Performance Modules for Advanced Workflow Submission. Soláň: 2022. p. 0-0.
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MATOUŠEK, R.; HŮLKA, T. Stabilization of Higher Periodic Orbits of the Duffing Map using Meta-evolutionary Approaches: A Preliminary Study. In 2022 IEEE Congress on Evolutionary Computation (CEC). IEEE Congress on Evolutionary Computation (CEC). Padova, Italy: IEEE, 2022. p. 1-8. ISBN: 978-1-7281-8393-0.
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KŮDELA, J.; NEVORAL, T.; HOLOUBEK, T. Comparing the Brain Storm Optimization Algorithm on the Ambiguous Benchmark Set. In Advances in Swarm Intelligence. ICSI 2022, Part II. Lecture Notes in Computer Science, vol 13344. Springer, Cham, 2022. p. 367-379. ISBN: 978-3-031-09726-3.
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KŮDELA, J.; NEVORAL, T.; HOLOUBEK, T. Composite Evolutionary Strategy and Differential Evolution Method for the ICSI’2022 Competition. In Advances in Swarm Intelligence. ICSI 2022, Part II. Lecture Notes in Computer Science, vol 13345. Springer, Cham, 2022. p. 432-439. ISBN: 978-3-031-09726-3.
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KŮDELA, J.; HOLOUBEK, T.; NEVORAL, T. Surrogate-Assisted Differential Evolution-Based Method for the ICSI’2022 Competition. In Advances in Swarm Intelligence. ICSI 2022, Part II. Lecture Notes in Computer Science, vol 13345. Springer, Cham, 2022. p. 440-449. ISBN: 978-3-031-09726-3.
Detail

Responsibility: Chlebík Jakub, Ing.