You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: SURVEY OF DYNAMIC SCHEDULING IN MANUFACTURING SYSTEMS 
Chapter Title:  Mediator Architectures 
1. Abstract of Cited Paper (BIB001):  Flexible manufacturing systems (FMS) have been developed with the hope that they would provide a means to tackle a threefold challenge — better quality, lower cost and shorter lead times — by integrating machine tools, robots, material handling and storage systems, and computers. Control of the integrated system presented a new set of problems as well as challenges, which have been receiving considerable attention from the academic community as well as from industrial system users. Intelligent control, which involves using computers to assist in decision making at various stages of the control process, has been advocated by many researchers as a possible avenue to reach a solution to these problems. This paper provides a review of the state of the art in intelligent control of FMS, in an attempt to supplement earlier general reviews via a more focused perspective. The principles of several techniques, namely simulation, knowledge based, example based, petri nets, and hybrid approaches are briefly introduced, and publications are reviewed, followed by discussions ontheir potential. Suggestions for further research and development are also enumerated. 
2. Abstract of Cited Paper (BIB002):  Abstract A Holonic Manufacturing System (HMS) is a manufacturing system where key elements, such as machines, cells, factories, parts, products, operators, teams, etc., are modeled as `holons' having autonomous and cooperative properties. The decentralized information structure, the distributed decision-making authority, the integration of physical and informational aspects, and the cooperative relationship among holons, make the HMS a new paradigm, with great potential for meeting today's agile manufacturing challenges. Critical issues to be investigated include how to define holons for a given problem context, what should be the appropriate system architecture, and how to design effective cooperation mechanisms for good system performance. In this paper, holonic scheduling is developed for a factory consisting of multiple cells. Relevant holons are identified, and their relationships are delineated through a novel modeling of the interactions among parts, machines, and cells. The cooperation mechanisms among holons are established based on the pricing concept of market economy following `Lagrangian relaxation' of mathematical optimization, and cooperation across cells is performed without accessing individual cells' local information nor intruding on their decision authority. The system also possesses structural recursivity and extendibility. Numerical testing shows that the method can generate near-optimal schedules with quantifiable quality in a timely fashion, and has comparable computational requirements and performance as compared to the centralized method following single-level Lagrangian relaxation. The method thus provides a theoretical foundation for guiding the cooperation among holons, leading to globally near-optimal performance. 
3. Abstract of Cited Paper (BIB003):  Global competition and rapidly changing customer requirements are forcing major changes in the production styles and configuration of manufacturing organizations. Traditional centralized manufacturing systems are not able to meet such requirements. This paper proposes an agent-based approach for dynamically creating and managing agent communities in such widely distributed and everchanging manufacturing environments. After reviewing the research literature, an adaptive multi-agent manufacturing system architecture called MetaMorph is presented and its main features are described. Such architecture facilitates multi-agent coordination by minimizing communication and processing overheads. Adaptation is facilitated through organizational structural change and two learning mechanisms: learning from past experiences and learning future agent interactions by simulating future dynamic, emergent behaviours. The MetaMorph architecture also addresses other specific requirements for next generation manufacturing sys... 
4. Abstract of Cited Paper (BIB004):  Modelling Manufacturing Systems: an Introduction: P. Brandimarte, A. Villa: Introduction and Overview of the Contributions.- For Further Reading.- References.- From the Aggregate Plan to Lot-Sizing in Multi-level Production Planning: J.-C. Hennet: Introduction.- The Planning Process.- The Lot-Sizing Problem.- Example.- Conclusion.- References.- Shop Floor Scheduling in Discrete Parts Manufacturing: G. J. Meester, J. M. J. Schutten, S. L. van de Velde, W. H. M. Zijm: Introduction.- Basic Decomposition Approach.- Multi-Resource Scheduling.- Set-Up Times.- Convergent and Divergent Job Routings.- Further Extensions and Practical Aspects.- JOBPLANNER.- Conclusions.- References.- Appendix A: Derivation of Set-Up Jobs.- Integrating Layout Design and Material Flow Management in Assembly Systems: M. Lucertini, D. Pacciaretti, A. Pacifici: Introduction.- Statement of the Problem.- Feasibility Properties.- Optimization Properties.- Conclusions.- References.- Appendix: Proofs of Theorems.- Reactive Scheduling in Real Time Production Control: E. Szelke, L. Monostori: Reactive Operation Management - Predictive, Reactive and Proactive Scheduling.- Models of Reactive and Proactive Scheduling Problems.- Solution Approaches - Methods, Techniques, Tools.- Conclusions: Future Research Issues in the Field.- References.- Simulation within CAD-Environment: P. Kopacek, G. Kronreif, T. Perme: Introduction.- Simulation System LASIMCO.- Simulation in Robotics - ROMOBIL/SITAR.- Conclusion.- References.- Model of Material Handling and Robotics.- C.-Y. Huang: Introduction.- Traditional Models of Material Handling and Robotics.- Facility Description Language (FDL).- Concurrent Flexible Specifications (CFS) for Material Handling and Robotics.- Discussion and Conclusion.- References.- A Simultaneous Approach for IMS Design: a Possibility Based Approach: G. Perrone, S. Noto La Diega: Introduction.- The Decisional Environment for Strategic IMS Design.- The Strategic IMS Design Decision-Making Tool: The Possibilistic Programming Theory.- The Possibilistic Framework for Strategic FMS Design.- Numerical Example.- Conclusions.- References.- Adaptive Production Control in Modern Industries: K. N. McKay, J. A. Buzacott: Introduction.- Motivation - Inherent Uncertainty.- Applying Production Control Methods - A Perspective.- Production Control Concepts for Immaturity or Uncertainty.- Conclusion.- Acknowledgments.- References. 
5. Abstract of Cited Paper (BIB005):  Abstract This discussion paper examines the role of hierarchy within the domain of shop floor control in manufacturing plants. Specifically, three distinct structures for shop floor control are considered, namely, hierarchical, heterarchical and holonic control systems. Holonic manufacturing is a novel paradigm for manufacturing that tries to merge the best properties of both hierarchical and heterarchical systems, namely, a high and predictable performance with a high robustness against disturbances. The paper identifies the concept of hierarchy in distributed shop floor control as one of the key contributions of holonic manufacturing. In a holonic architecture, the mapping of functions to control units remains flexible, such that decision power can be distributed over these units as needed. Based on the invariants concept of computer science, a modelling framework is proposed to identify the decision making needs of each unit. It can be used not only to describe the behaviour of the system, but also to impose performance and operational guarantees. 
6. Abstract of Cited Paper (BIB006):  The paper provides a first experimental contribution to the validation and comparison of multi-agent heterarchical architectures in order to point out their limits, their main peculiarities and real applicability. For this purpose, the behaviours of two particular control solutions, characterised by a different degree of decision-making delegation assigned to physical and information units in the production system, have been simulated. The experimental campaign is divided into three trials, in order to measure the performances of the two architectures not only under stable and predictable conditions, but also in case of unexpected events, such as the release of urgent manufacturing orders and the occurrence of failures in production resources. 
7. Abstract of Cited Paper (BIB007):  Distributed manufacturing systems are more flexible in their arrangement and use of their resources. This permits a more dynamic and opportunistic allocation of manufacturing resources to work elements than is possible with today's centralized allocation systems. However, unlike solving the problem from a single solver view, there is no absolute control or tight coordination over how and when to decompose the problem, when to undertake a solution or the procedure for verifying consistency. Such activities will largely be left to the distributed entities to decide either individually or jointly. As a consequence the resulting allocations may suffer and induce myopic behaviour lacking in stability and regularity in the performance of the total system. Thus, the issues connected with solving the problem often move beyond the pure algorithmic focus of computation to include how the problem is decomposed, how or to whom it is assigned, and the organization for solving the subproblems, strategies used for resol... 
8. Abstract of Cited Paper (BIB008):  Abstract The requirement for adaptable and re-configurable control systems for manufacturing has highlighted the inadequacies of traditional centralised control approaches, leading researchers to focus on decentralised approaches. The question of what is the most appropriate control architecture for a given system has led industrial and academic researchers to develop a spectrum of decentralised control architectures ranging from hierarchical to non-hierarchical structures. While current research has confirmed the potential of decentralised architectures, neither extreme of this control architecture spectrum has proven to be the most appropriate choice for a given manufacturing system. Recent research into providing an objective comparison of alternative control architectures has shown that some degree of hierarchy is important for distributed manufacturing control architectures. This paper is concerned with our current investigations into why these partial hierarchies appear to display superior performance. 
9. Abstract of Cited Paper (BIB009):  Agent technology has been considered as an important approach for developing distributed intelligent manufacturing systems. A number of researchers have attempted to apply agent technology to manufacturing enterprise integration, supply chain management, manufacturing planning, scheduling and control, materials handling, and holonic manufacturing systems. This paper gives a brief survey of some related projects in this area, and discusses some key issues in developing agent-based manufacturing systems such as agent technology for enterprise integration and supply chain management, agent encapsulation, system architectures, dynamic system reconfiguration, learning, design and manufacturability assessments, distributed dynamic scheduling, integration of planning and scheduling, concurrent scheduling and execution, factory control structures, potential tools and standards for developing agent-based manufacturing systems. An extensive annotated bibliography is provided.

Literature Review:
Despite the good performance of autonomous architectures, usually they face problems in providing globally optimised schedules and predictability in the presence of a large number of agents, such as virtual enterprises (Brennan and Norrie, 1998; BIB010 BIB006 Shen et al., 2001; BIB008 ). Several researchers have proposed mediator architectures for dynamic scheduling in such complex environments to combine robustness, optimality, and predictability. A mediator architecture has a basic structure consisting of autonomous cooperating local agents that are capable of negotiation with each other in order to achieve production targets BIB003 BIB010 BIB006 Shen et al., 2001) . This basic structure is extended with mediator agents to coordinate the behaviour of the local agents to perform global dynamic scheduling, see Figure 4 . The mediator agents operate concurrently with local agents and contribute to the same decision making processes as the local agents. The local agents maintain their decision making autonomously, but may request advice from the mediator agent. This agent has the ability to advise, impose or update decisions taken by the resource agents in order to satisfy the global objectives and resolve the conflict situations. In this way the mediator agent can coordinate and influence the overall behaviour of the system. The mediator agent has an overview of the entire system, while the local agents can have a more detailed, more correct and more up-todate view of the local situations. As such, local agents can react more quickly to disturbances, while mediator agents can coordinate the agents' behaviour and often improve the global performance. The mediator architecture provides computational simplicity, while being quite suitable for developing distributed industrial systems that are complex, dynamic, and composed of a large number of resource agents. BIB009 , BIB006 , BIB007 showed in their comparative studies that mediator architectures have improved performance relative to autonomous architectures, because of their ability to plan further in the future in combination with their ability to react to disturbances, which can result in globally satisfactory performance. Very basic mediator architecture was proposed by BIB001 for dynamic scheduling in flexible manufacturing systems. The architecture is composed of task agents, task manager agent, resource agents, and resource mediator agent. Task manager agent creates the task agents. The resource mediator agent negotiates with the resource agents using the contract net protocol the execution the tasks. When failures occur on the resources, message on the operations in failure are sent to the mediator resource agent, which proceeds to a renegotiation process with other resource agents. This mode of handling the failures is quite simple. For an increased robustness in complex manufacturing systems, some authors proposed the integration of mediator agents to each level of the manufacturing facility. BIB004 proposed the mediator architecture Metaphor I, for dynamic scheduling of large heterogeneous manufacturing systems to address virtual enterprise issues combining sub-tasking and virtual clustering of agents. Virtual enterprise partnership issues are associated with the unification of heterogeneous manufacturing subsystems into a large, dynamic virtual coalition of co-operative subsystems. There are two main types of agents in the architecture: resource agents and mediator agents. Resource agents are used to represent manufacturing devices and operations, while mediator agents are used to coordinate the resource agents using the contract net protocol. Malfunctioning of a resource agent is kept at a local level. A resource breakdown is simulated by introducing a breakdown period into the resource. Each job allocated within the halt-period is rescheduled to other available time slots found in the same resource (the malfunctioning resource) or in a different resource. Based on Metaphor I,  developed Metaphor II, for integrating the manufacturing enterprise's activities such as design, planning, scheduling, simulation, execution, material supply, and marketing services. In this architecture the manufacturing system is organised through a hierarchy of subsystem mediators. Four types of mediators were introduced: enterprise, resource, marketing, and design mediators. Each subsystem is an agent-based system integrated into the system through a special mediator. The manufacturing resource agents are coordinated by appropriate mediators at all levels of the system. sickness during the production process. Match up rescheduling strategy and agent-based collaboration are used to repair only part of the originally created schedule for improving the reactive scheduling efficiency, while maintaining the scheduling quality. Suresh and Chaudri (1993) , BIB002 ,  , and BIB005 .