Multi-Agent-Based Production Planning and Control - Hardcover

Über die Autorin bzw. den Autor

PROFESSOR JIE ZHANG, School of Mechanical Engineering, Shanghai Jiao Tong University, Shanghai, China. Professor Zhang achieved her PhD in 1997 from the School of Electrical Engineering, Nanjing University of Aeronautics and Astronautics, China and in 2008-2009 she was Visiting Research Fellow at the Department of Industrial Engineering and Operations Research, University of California, Berkeley, USA. She is the author of five books in Chinese and over 100 peer-reviewed journal and transaction full papers in English and Chinese. She holds regular lectures at Shanghai Jiao Tong University in computer integrated manufacturing systems, enterprise resource planning, E-operation management systems for future manufacturing, the foundations for manufacturing design, and manufacturing systems and information technologies. Since 2010 she has been Executive Director of the Production System Council, Chinese Mechanical Engineering Society of Manufacturing Engineering.

Von der hinteren Coverseite

At the crossroads of artificial intelligence, manufacturing engineering, operational research and industrial engineering and management, multi-agent-based production planning and control is an intelligent and industrially crucial technology with increasing importance. This book provides a complete overview of multi-agent-based methods for today's competitive manufacturing environment, including the Job Shop Manufacturing and Re-entrant Manufacturing processes. In addition to the basic control and scheduling systems, the author also highlights advance research in numerical optimization methods and wireless sensor networks and their impact on intelligent production planning and control system operation.

• Enables students, researchers and engineers to understand the fundamentals and theories of multi-agent-based production planning and control
• Written by an author with more than 20 years' experience in studying and formulating a complete theoretical system in production planning technologies
• Fully illustrated throughout, the methods for production planning, scheduling and controlling are presented using experiments, numerical simulations and theoretical analysis

Comprehensive and concise, Multi-Agent-Based Production Planning and Control is aimed at the practicing engineer and graduate student in industrial engineering, operational research, and mechanical engineering. It is also a handy guide for advanced students in artificial intelligence and computer engineering.

Aus dem Klappentext

At the crossroads of artificial intelligence, manufacturing engineering, operational research and industrial engineering and management, multi-agent-based production planning and control is an intelligent and industrially crucial technology with increasing importance. This book provides a complete overview of multi-agent-based methods for today's competitive manufacturing environment, including the Job Shop Manufacturing and Re-entrant Manufacturing processes. In addition to the basic control and scheduling systems, the author also highlights advance research in numerical optimization methods and wireless sensor networks and their impact on intelligent production planning and control system operation.

• Enables students, researchers and engineers to understand the fundamentals and theories of multi-agent-based production planning and control
• Written by an author with more than 20 years' experience in studying and formulating a complete theoretical system in production planning technologies
• Fully illustrated throughout, the methods for production planning, scheduling and controlling are presented using experiments, numerical simulations and theoretical analysis

Comprehensive and concise, Multi-Agent-Based Production Planning and Control is aimed at the practicing engineer and graduate student in industrial engineering, operational research, and mechanical engineering. It is also a handy guide for advanced students in artificial intelligence and computer engineering.