Scheduling problems concern the allocation of limited resources over time among both parallel and sequential activities. The majority of these problems belong to the class of NP-hard. Agent-based approaches have been recently applied to solve some of these difficult problems, particularly distributed scheduling problems. Load balancing has been adopted as an optimization criterion for several scheduling problems. However, in many practical situations, a load balanced solution may not be feasible or attainable. To deal with this limitation, this paper presents a generic mathematical model of load distribution for resource allocation, called desired load distribution. The objective is to develop a model for scheduling of general parallel machines that can be used both in centralized resource management settings and in agent-based distributed scheduling systems. Unlike many existing agent-based scheduling systems, this model attempts to obtain a global optimal solution through many-to-many task/resource allocation instead of one-to-many negotiation approaches.
This paper proposes a new method of analyzing the solution space of multi-factor manufacturing scheduling problems. The proposed method is introduced together with two new concepts: relation matrix and decision matrix. This method simplifies a multi-factor problem into a number of two-factor sub-problems which are then analyzed individually. Some close-expressions of the number of feasible solutions for multi-device, multi-worker and multi-task are obtained. It can be used not only to calculate the number of possible/feasible solutions, but also to obtain these solutions in simple cases. It is particularly useful in very complex situations, since the results of solution space analysis can help choose appropriate techniques or algorithms to solve complex scheduling problems.
Previously, we reported some preliminary results of our long-term research work on iShopFloor (Intelligent Shop Floor). This paper reports some of our recent work on the implementation of XML-based message services for Internet-based intelligent shop floors. The objective is to investigate XML for message exchange among Internet-based shop floor devices that are represented by intelligent agents. The paper discusses the advantages of using XML for message services and presents our initial implementation. From this implementation, we have seen some advantages, including: (1) simplification and standardization of message services in Internet-based intelligent shop floors; (2) facilitation of the integration of an agent-based scheduling system with other intelligent shop floor systems, including Web-based shop floor monitoring and control systems, etc.
This paper presents some results of our recent research work related to the development of a new Collaborative Agent System Architecture (CASA) and an Infrastructure for Collaborative Agent Systems (ICAS). Initially being proposed as a general architecture for Internet based collaborative agent systems (particularly complex industrial collaborative agent systems), the proposed architecture is very suitable for managing the Internet enabled complex supply chain for a large manufacturing enterprise. The general collaborative agent system architecture with the basic communication and cooperation services, domain independent components, prototypes and mechanisms are described. Benefits of implementing Internet enabled supply chains with the proposed infrastructure are discussed. A case study on Internet enabled supply chain management is presented.
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