Hyper-heuristics (HHs) stand as a relatively recent approach to solving optimization
problems. There are different kinds of HHs. One of them deals with how low-level heuristics …

Economic globalization has transformed many manufacturing enterprises from a single-plant
production mode to a multi-plant cooperative production mode. The distributed flexible job …

In this paper, Deep Q-Network (DQN) was adopted to solve the Job shop Scheduling
Problem (JSP) in the smart factory process. On the other hand, cloud computing has …

This paper presents a hybrid genetic algorithm with collective communication (HGACC)
using distributed processing for the job shop scheduling problem. The genetic algorithm …

Problem instances are paramount when testing the performance of any learning algorithm.
For this reason, it is customary to use widespread problems known as benchmark instances …

The Job-Shop Scheduling Problem represents a challenging field of study due to its NP-
Hard nature. Its many industrial and practical, real-world applications skyrocket its …

This study presents an offline learning Simulated Annealing approach to generate a
constructive hyper-heuristic evaluated through training and testing on a set of instances for …

Abstract Job Shop Scheduling problems have become popular because of their many
industrial and practical applications. Among the many solving strategies for this problem …

Featured Application This research allows improving the schedule of jobs in manufacturing
workshops and this increases the amount of products without having the need to increase …

Job shop scheduling problems (JSSPs) have been the subject of intense studies for
decades because they are often at the core of significant industrial planning challenges and …