This book takes a close look at recent progress in the field of supply chain management using agent technology and more specifically multiagent systems. Sixteen chapters are organized in four main parts: Introductory Papers; Multiagent Based Supply Chain Modeling; Collaboration and Coordination Between Agents in a Supply Chain; and Multiagent Based Supply Chain Management: Applications. The result is a comprehensive review of existing literature, and ideas for future research.
Industries and particularly the manufacturing sector have been facing difficult challenges in a context of socio-economic turbulence characterized by complexity as well as the speed of change in causal interconnections in the socio-economic environment. In order to respond to these challenges companies are forced to seek new technological and organizational solutions. In this context two main characteristics emerge as key properties of a modern automation system – agility and distribution. Agility because systems need not only to be flexible in order to adjust to a number of a-priori defined scenarios, but rather must cope with unpredictability. Distribution in the sense that automation and business processes are becoming distributed and supported by collaborative networks. Emerging Solutions for Future Manufacturing Systems includes the papers selected for the BASYS’04 conference, which was held in Vienna, Austria in September 2004 and sponsored by the International Federation for Information Processing (IFIP).
This dissertation, "Modeling and Solving Decentralized Supply Chain Management Problems Using Multi-agent System With Dynamic-control Agents" by Wan-hin, Derek, Chau, 鄒允軒, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Managing large scale supply chains are never an easy task. Numerous researches have put emphasis on supply chain modeling and optimization to assist businesses in searching for the best practices so as to endure the extremely competitive business landscape. To some, the paradigm of centralized supply chain management is adequate for solving its strategic and operational problems. Yet with the improper use of authoritative assumptions, the efficiency of the management process is often jeopardized. Furthermore, current researches in decentralized supply chain are mostly focused on dyadic or linear relationship and seldom consider quantitative modeling and analysis with scalability. Recent development in multi-agent systems provided a means for such a modeling methodology and hence researches in this area. To enhance model representativeness and computational efficiency, vision-based control models that are able to simulate individual operational and strategic traits are developed. In this research, pyramidal agent alignment is proposed for simulating the management-operation dimension with regards to decision exercising and bargaining power management. The system offers one thousand supply chain agents that are simulated in a mono-layer, multi-tier network in real time. Stochastic and dynamic behaviors of the network are handled by statistical regression on scenario-based model evaluation. The proposed design enabled grand scale supply chain modeling and optimization that follows a general or custom simulation supported optimization architecture. Network governance problems and dynamic steering problems are considered and solved using genetic algorithm and dynamic programming. The thesis looks into the potential benefits and limitations of the proposed methods in details, and future research directions are discussed. DOI: 10.5353/th_b5387964 Subjects: Business logistics - Management Multiagent systems
Because of their mutually influencing interactions, information systems and modern manufacturing systems are intertwined. They have been so integrated that information systems have become an embedded and critical component of any effective manufacturing system. The impact of the increasing focus on information permeates throughout the manufacturing life cycle, from product conceptualization, design, process planning, all the way to production, order fulfilment, and customer services. For these reasons, it is critical that we study information-based manufacturing in its entirety, crossing the traditional functional boundaries and building as much synergy between Information Systems (IS), Information Technology (IT), and manufacturing as possible. This is the motivation for this book and, to this end, the purpose of this book is threefold: to establish an up-to-date interdisciplinary research framework for information-based manufacturing that builds on the research foundation from IS and IT and manufacturing research; to develop a forward-looking research agenda for information-based manufacturing for identifying future directions for research and applications; and to foster a joint academic and industrial research agenda in information systems and manufacturing by identifying the greatest synergy possible between academic research and industrial practices.
"This book is a compilation of advanced research results in architecture and modeling issues of multi-agent systems. It serves as a reference for research on system models, architectural design languages, methods and reasoning, module interface design, and design issues"--Provided by publisher.
"Supply Chain Event Management (SCEM)" is one of the major topics in application-oriented Supply Chain Management. However, many solutions lack conceptual precision and currently available client-server SCEM-systems are ill-suited for complex supply networks in today's business environment. Agent-based proactive information logistics promises to overcome existing deficits by providing event-related information to all participants in the distributed environment. Hence, follow-up costs of disruptive events are significantly reduced for all network participants and performance of a supply network is increased. In this book a thorough analysis of the event management problem domain is the starting point to develop a generic agent-based approach to Supply Network Event Management. The main focus lies on practical issues of event management (e.g., semantic interoperability) and economic benefits to be achieved with agent technology in this state-of-the-art problem domain.
This book describes the implementation of autonomous control with multiagent technology. Therewith, it tackles the challenges of supply network management caused by the complexity, the dynamics, and the distribution of logistics processes. The paradigm of autonomous logistics reduces the computational complexity and copes with the dynamics locally by delegating process control to the participating objects. As an example, shipping containers may themselves plan and schedule their way through logistics networks in accordance with objectives imposed by their owners. The technologies enabling autonomous logistics are thoroughly described and reviewed. The presented solution has been used in a realistic simulation of real-world container logistics processes. The validation shows that autonomous control is feasible and that it outperforms the previous centralised dispatching approach by significantly increasing the resource utilisation efficiency. Moreover, the multiagent system relieves human dispatchers from dealing with standard cases, giving them more time to solve exceptional cases appropriately.
The book is concerned with the application of basic concepts of Agent-based technology for the flow of information between various components of the supply chain formed for a manufacturing organization with following objectives: • Identifying issues related to sharing information as the most critical factor in supply chain activities • Addressing problems associated with sharing information both within and between different organizations • Sharing effective information by formulating an agent-based framework for supply chain management activities • To enhance the effectiveness of Supply chain management activities
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.
