Job shop scheduling problems (JSSPs) represent a critical and challenging class of
combinatorial optimization problems. Recent years have witnessed a rapid increase in the …

Abstract Machine scheduling aims to optimally assign jobs to a single or a group of
machines while meeting manufacturing rules as well as job specifications. Optimizing the …

Evolutionary algorithms (EA), a class of stochastic search methods based on the principles
of natural evolution, have received widespread acclaim for their exceptional performance in …

Dynamic scheduling plays a pivotal role in smart manufacturing by enabling real-time
adjustments to production schedules, thereby enhancing system resilience and promoting …

The unpredictable variety of dynamic events in manufacturing systems poses a great
challenge for tackling the job-shop scheduling problem (JSP), while most prior arts fail to …

This manuscript introduces an innovative approach to optimizing the distribution of a limited
vaccine resource within a population modeled as a contact network, aiming to mitigate the …

Amidst the global energy crisis, the industrial sector is facing unparalleled energy
conservation challenges as a primary energy consumer. Industrial demand response (IDR) …

This paper extends a novel model for modern flexible manufacturing systems: the multi-
objective dynamic partial-re-entrant hybrid flow shop scheduling problem (MDPR-HFSP) …

A distributed flexible flowshop problem (DFFSP) has been extensively studied over recent
years. It is assumed that all jobs to be processed are exactly known in advance, and …

This paper studies the flexible double shop scheduling problem (FDSSP) that considers
simultaneously job shop and assembly shop. It brings about the problem of scheduling …