[
[1] Budi, H. S., et al. Development of an adaptive genetic algorithm to optimize the problem of unequal facility location. Foundations of Computing and Decision Sciences, 47, 2, 2022.
]Search in Google Scholar
[
[2] Dastan, M., Davoodi, S. M. R., Karbassian, M., and Moeini, S. Developing a mathematical model for a green closed-loop supply chain with a multi-objective gray wolf optimization algorithm. Foundations of Computing and Decision Sciences, 47, 2, 2022.
]Search in Google Scholar
[
[3] Ding, H., Liu, Y., Zhang, Y., Wang, S., Guo, Y., Zhou, S., Liu, C. Data-driven evaluation and optimization of the sustainable development of the logistics industry: case study of the Yangtze River Delta in China. Environmental Science and Pollution Research, 2022, 1-15.10.1007/s11356-022-20624-0909607235554806
]Search in Google Scholar
[
[4] Goli, A., Tirkolaee, E. B., Weber, G. W. A perishable product sustainable supply chain network design problem with lead time and customer satisfaction using a hybrid whale-genetic algorithm. In Logistics operations and management for recycling and reuse. Springer, Berlin, Heidelberg, 2020, 99-124.10.1007/978-3-642-33857-1_6
]Search in Google Scholar
[
[5] Noer, Z., et al. A new model for scheduling operations in modern agricultural processes Foundations of Computing and Decision Sciences, 47, 2, 2022.
]Search in Google Scholar
[
[6] Pan, Y. H., Qu, T., Wu, N. Q., Khalgui, M., Huang, G. Q. Digital twin based real-time production logistics synchronization system in a multi-level computing architecture. Journal of Manufacturing Systems, 58, 2021, 246-260.10.1016/j.jmsy.2020.10.015
]Search in Google Scholar
[
[7] Ren, S., Zhang, Y., Liu, Y., Sakao, T., Huisingh, D., Almeida, C. M. A comprehensive review of big data analytics throughout product lifecycle to support sustainable smart manufacturing: A framework, challenges and future research directions. Journal of Cleaner Production, 210, 2019, 1343-1365.10.1016/j.jclepro.2018.11.025
]Search in Google Scholar
[
[8] Syah, R., et al. Design a multi period closed-loop supply chain program to supply recycled products. Foundations of Computing and Decision Sciences, 47, 2, 2022.
]Search in Google Scholar
[
[9] Syah, R., et al. Optimizing the multi-level location-assignment problem in queue networks using a multi-objective optimization approach. Foundations of Computing and Decision Sciences, 47, 2, 2022.
]Search in Google Scholar
[
[10] Syah, R., et al. Designing a green supply chain transportation system for an automotive company based on bi-objective optimization. Foundations of Computing and Decision Sciences, 47, 2, 2022.
]Search in Google Scholar
[
[11] Tikhonov, A. I., Sazonov, A. A., Kraev, V. M., and Kuzmina-Merlino, I. The Main Trends and Challenges in the Development of the Di erent Industries During the COVID-19 Pandemic. Foundations of Computing and Decision Sciences, 47, 2, 2022.
]Search in Google Scholar
[
[12] Tirkolaee, E. B., Goli, A., Weber, G. W., Szwedzka, K. A novel formulation for the sustainable periodic waste collection arc-routing problem: A hybrid multi-objective optimization algorithm. In Logistics Operations and Management for Recycling and Reuse, Springer, Berlin, Heidelberg, 2020, 77-98.10.1007/978-3-642-33857-1_5
]Search in Google Scholar
[
[13] Umeuzuegbu, J. C., Okiy, S., Nwobi-Okoye, C. C., Onukwuli, O. D. Computational modeling and multi-objective optimization of engine performance of biodiesel made with castor oil. Heliyon, 7, 3, 2021.
]Search in Google Scholar
[
[14] Verma, S., Sharma, R., Deb, S., Maitra, D. Artificial intelligence in marketing: Systematic review and future research direction. International Journal of Information Management Data Insights, 1, 1, 2021.
]Search in Google Scholar
