In recent years, there has been a growing research interest in integrating machine learning
techniques into meta-heuristics for solving combinatorial optimization problems. This …

The flexible job shop scheduling problem (FJSP) is significant for realistic manufacturing.
However, the job processing time usually is uncertain and changeable during …

A large number of intelligent algorithms based on social intelligent behavior have been
extensively researched in the past few decades, through the study of natural creatures, and …

This paper aims at integrating machine learning techniques into meta-heuristics for solving
combinatorial optimization problems. Specifically, our study develops a novel efficient …

This study develops intelligent inventory management (IIM) approaches for managing
perishable pharmaceutical products in a healthcare supply chain consisting of multiple …

The elephant herding optimization (EHO) is a recent swarm intelligence algorithm. This
algorithm simulates the clan updating and separation behavior of elephants. The EHO …

The job sequencing and tool switching problem is a combinatorial optimisation problem that
appears in various industries, mainly in the manufacturing sector. Although tool switching is …

Researchers have been studying genetic algorithms (GAs) extensively in recent decades
and employing them to address extremely challenging combinatorial optimization problems …

Featured Application The proposed algorithm for painting large objects based on a nine-axis
UR5 robotic manipulator can be applicable in many automobile repair shops where paint …

This paper presents a mixed-model sequencing problem with stochastic processing times
(MMSPSP) in a multi-station assembly line. A new mixed-integer nonlinear programing …