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Towards Interpretable Dispatching Rules: Application of Expression Simplification Methods.

, , and . SSCI, page 1-8. IEEE, (2021)

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Heuristic and Metaheuristic Methods for the Unrelated Machines Scheduling Problem: A Survey., and . CoRR, (2021)Selection of dispatching rules evolved by genetic programming in dynamic unrelated machines scheduling based on problem characteristics., and . J. Comput. Sci., (2022)Automatic design of dispatching rules for static scheduling conditions., and . Neural Comput. Appl., 33 (10): 5043-5068 (2021)Novel ensemble collaboration method for dynamic scheduling problems., , , and . GECCO, page 893-901. ACM, (2022)Solving the Dial-a-Ride Problem Using an Adapted Genetic Algorithm., , , and . AI*IA, volume 13196 of Lecture Notes in Computer Science, page 689-699. Springer, (2021)On the Evolution of Boolean Functions with the Algebraic Normal Form Representation., , , and . GECCO Companion, page 639-642. ACM, (2024)Constructing Ensembles of Automatically Designed Relocation Rules for the Container Relocation Problem., , and . CEC, page 1-8. IEEE, (2024)Comparison of solution representations for scheduling in the unrelated machines environment., and . MIPRO, page 1336-1342. IEEE, (2016)Comparison of schedule generation schemes for designing dispatching rules with genetic programming in the unrelated machines environment., and . Appl. Soft Comput., (2020)Comparison of ensemble learning methods for creating ensembles of dispatching rules for the unrelated machines environment., and . Genet. Program. Evolvable Mach., 19 (1-2): 53-92 (2018)