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 …

Scheduling has an immense effect on various areas of human lives, be it though its
application in manufacturing and production industry, transportation, workforce allocation, or …

Dynamic Flexible Job Shop Scheduling (DFJSS) is a critical combinatorial optimisation
problem known for its dynamic nature and flexibility of machines. Traditional scheduling …

At present, a lot of references use discrete event simulation to evaluate the fitness of evolved
rules, but which simulation configuration can achieve better evolutionary rules in a limited …

Resource constrained project scheduling problem is an NP-hard problem that attracts many
researchers because of its complexity and daily use. In literature there are a lot of various …

Abstract Evolutionary Ensemble Learning (EEL) provides a general approach for scaling
evolutionary learning algorithms to increasingly complex tasks. This is generally achieved …

Priority rules are one of the most common and popular approaches to real-time scheduling.
Over the last decades, several methods have been developed to generate rules …

The container relocation problem is a challenging combinatorial optimisation problem
tasked with finding a sequence of container relocations required to retrieve all containers by …

Scheduling problems constitute an important part in many everyday systems, where a
variety of constraints have to be met to ensure the feasibility of schedules. These problems …

Dynamic flexible job shop scheduling is an important but difficult combinatorial optimization
problem that has numerous real-world applications. Genetic programming (GP) has been …