LISS 2020

Proceedings of the 10th International Conference on Logistics, Informatics and Service Sciences
1. Auflage 2021
ISBN: 978-981-334-358-0
Verlag: Springer Nature Singapore

Buch, Englisch, 1056 Seiten, Format (B × H): 160 mm x 241 mm, Gewicht: 1742 g

This book contains the proceedings of the 10th International Conference on Logistics, Informatics and Service Sciences (LISS 2020), which is co-organized by Beijing Jiaotong University, Budapest University of Technology and Economics, in July 25–28 2020. This book focuses on the “AI and data-driven technical and management innovation in logistics, informatics and services” and aims to provide new research methods, theories and applications from various areas of management and engineering. In detail the included scientific papers analyse and describe communication processes in the fields of logistics, informatics, service sciences and other related areas. The variety of papers delivers added value for both scholars and practitioners. Information and communication technologies have been providing an effective network infrastructure and development platform for logistics and service operations.

Zielgruppe

Research

Autoren/Hrsg.

Liu, Shifeng

Bohács, Gábor

Huang, Anqiang

Shi, Xianliang

Shang, Xiaopu

Fachgebiete

• Wirtschaftswissenschaften Betriebswirtschaft Bereichsspezifisches Management Einkauf, Logistik, Supply-Chain-Management
• Wirtschaftswissenschaften Betriebswirtschaft Wirtschaftsinformatik, SAP, IT-Management
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Wirtschaftsinformatik

Inhaltsverzeichnis

Mono camera based pallet detection and pose estimation for Automated Guided Vehicles.- A Review of the Schedulability Tests and Optimal Design for Rate-Monotonic Scheduling.- Content Recommendation of Tender Documents Based on Qualitative Characteristics.- Data-Driven Phenetic Modeling of Scripts’ Evolution.- MPNC: Improving Reliability of Data Transmission in Wireless Ad Hoc Networks.- Research on Bidding Case Recommendation Algorithm Considering Bidding Features.- Research on the Prediction of Shenzhen Growth Enterprise Market Price Index Based on EMDARIMA Model.- Research on Location and Path Planning of Distribution Center Based on Improved k-means Clustering Algorithm and Improved Ant Colony Algorithm.- Multiobjective optimization of production line supply based on maximum endurance time and rest allowance.- Intralogistics conversion of the Physical Internet.- Bayesian Production/Inventory Competition with Unobserved Lost Sales.