Learning dispatching rules via novel genetic programming with feature selection in energy-aware dynamic job-shop scheduling.

ABSTRACT: The incorporation of energy conservation measures into production efficiency is widely recognized as a crucial aspect of contemporary industry. This study aims to develop interpretable and high-quality dispatching rules for energy-aware dynamic job shop scheduling (EDJSS). In comparison to the traditional modeling methods, this paper proposes a novel genetic programming with online feature selection mechanism to learn dispatching rules automatically. The idea of the novel GP method is to achieve a progressive transition from exploration to exploitation by relating the level of population diversity to the stopping criteria and elapsed duration. We hypothesize that diverse and promising individuals obtained from the novel GP method can guide the feature selection to design competitive rules.

SUBMITTER: Sitahong A 

PROVIDER: S-EPMC10219999 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature