Large language models as evolutionary optimizers
Evolutionary algorithms (EAs) have achieved remarkable success in tackling complex
combinatorial optimization problems. However, EAs often demand carefully-designed …
combinatorial optimization problems. However, EAs often demand carefully-designed …
Survey on genetic programming and machine learning techniques for heuristic design in job shop scheduling
Job shop scheduling (JSS) is a process of optimizing the use of limited resources to improve
the production efficiency. JSS has a wide range of applications, such as order picking in the …
the production efficiency. JSS has a wide range of applications, such as order picking in the …
Surprisingly popular-based adaptive memetic algorithm for energy-efficient distributed flexible job shop scheduling
With the development of the economy, distributed manufacturing has gradually become the
mainstream production mode. This work aims to solve the energy-efficient distributed flexible …
mainstream production mode. This work aims to solve the energy-efficient distributed flexible …
Genetic programming with lexicase selection for large-scale dynamic flexible job shop scheduling
Dynamic flexible job shop scheduling is a prominent combinatorial optimisation problem
with many real-world applications. Genetic programming has been widely used to …
with many real-world applications. Genetic programming has been widely used to …
A genetic programming based cooperative evolutionary algorithm for flexible job shop with crane transportation and setup times
X Chen, J Li, Z Wang, J Li, K Gao - Applied Soft Computing, 2024 - Elsevier
Confronted with increasingly complex industrial scenarios, limited transportation resources
and complicated time constraints introduce significant challenges to production efficiency …
and complicated time constraints introduce significant challenges to production efficiency …
An enhanced memetic algorithm with hierarchical heuristic neighborhood search for type-2 green fuzzy flexible job shop scheduling
The green flexible job shop has received increasing attention due to the development of
modern industry and the improvement of environmental protection awareness. Meanwhile …
modern industry and the improvement of environmental protection awareness. Meanwhile …
Niching Genetic Programming to Learn Actions for Deep Reinforcement Learning in Dynamic Flexible Scheduling
Dynamic Flexible Job Shop Scheduling (DFJSS) is a critical combinatorial optimisation
problem known for its dynamic nature and flexibility of machines. Traditional scheduling …
problem known for its dynamic nature and flexibility of machines. Traditional scheduling …
Multitask linear genetic programming with shared individuals and its application to dynamic job shop scheduling
Multitask genetic programming methods have been applied to various domains, such as
classification, regression, and combinatorial optimization problems. Most existing multitask …
classification, regression, and combinatorial optimization problems. Most existing multitask …
Evolutionary multitask optimization in real-world applications: A survey
Because of its strong ability to solve problems, evolutionary multitask optimization (EMTO)
algorithms have been widely studied recently. Evolutionary algorithms have the advantage …
algorithms have been widely studied recently. Evolutionary algorithms have the advantage …
Knowledge-transfer based genetic programming algorithm for multi-objective dynamic agile earth observation satellite scheduling problem
The multi-objective dynamic agile earth observation satellite scheduling problem (MO-
DAEOSSP) aims to schedule a set of real-time arrival requests and form a reasonable …
DAEOSSP) aims to schedule a set of real-time arrival requests and form a reasonable …