Remanufacturing system scheduling of batch products with the consideration of dynamic changes in machine efficiency using an improved artificial bee colony algorithm

Jin, Qinyu; Zhang, Shuai; Xu, Jiyuan; Jiang, Kang; Cheng, Yuanzhe; Zhang, Wenyu

doi:10.1016/j.cie.2023.109817

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Remanufacturing system scheduling of batch products with the consideration of dynamic changes in machine efficiency using an improved artificial bee colony algorithm

Cited by 6 publications

References 41 publications

Lot-streaming in energy-efficient three-stage remanufacturing system scheduling problem with inequal and consistent sublots

Lot-streaming in energy-efficient three-stage remanufacturing system scheduling problem with inequal and consistent sublots

A multi-objective integrated scheduling of remanufacturing system considering time window constrained outsourcing option

Energy-aware remanufacturing process planning and scheduling problem using reinforcement learning-based particle swarm optimization algorithm

Contact Info

Product

Resources

About