1. bookVolumen 47 (2022): Edición 2 (June 2022)
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Formato
Revista
eISSN
2300-3405
Primera edición
24 Oct 2012
Calendario de la edición
4 veces al año
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access type Acceso abierto

Preface to the Special Issue on Computational Performance Analysis based on Novel Intelligent Methods: Exploration and Future Directions in Production and Logistics

Publicado en línea: 09 Jul 2022
Volumen & Edición: Volumen 47 (2022) - Edición 2 (June 2022)
Páginas: 107 - 110
Detalles de la revista
License
Formato
Revista
eISSN
2300-3405
Primera edición
24 Oct 2012
Calendario de la edición
4 veces al año
Idiomas
Inglés
Abstract

This special issue of the Foundations of Computing and Decision Sciences, titled “Computational Performance Analysis based on Novel Intelligent Methods: Exploration and Future Directions in Production and Logistics”, is devoted to the application of Computational Performance Analysis (CPA) for real-life phenomena. The special issue and its editorial present novel intelligent methods as they meet with various research topics in production and logistics, especially in terms of challenges, limitations and future trends. This special issue aims to bring together current progress on the CPA, organization management, and novel models and solution techniques that can contribute to a better understanding of the CPA systems and delineate useful practical strategies. Methodologically interesting and well-documented case studies are highly recommended. Additionally, the special issue covers innovative cutting-edge research methodologies and applications in the related research field.

[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

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