Negotiation Protocol Based on Budget Approach for Adaptive Manufacturing Scheduling

2012 ◽  
pp. 1517-1538
Author(s):  
Paolo Renna ◽  
Rocco Padalino

The research proposed concerns the development of a multi-agent scheduling approach able to support manufacturing systems in different dynamic conditions. The negotiation protocol defined budget approach is based on a financial asset that each part obtains when it is released into the manufacturing system for processing. The part spends the budget to perform the manufacturing operations by the workstations; the virtual market in which part agent and workstation agents coordinate the decentralized system. A fuzzy tool is proposed to assign the budget to each part based on the objectives pursued. A simulation environment based on Rockwell ARENA® platform has been developed in order to test the proposed approach. The simulations are used to compare the proposed approach with classical dynamical scheduling approaches proposed in literature. The results show how the proposed approach leads to better results, and it can be selective among the different priority of the parts.

Author(s):  
Paolo Renna ◽  
Rocco Padalino

The research proposed concerns the development of a multi-agent scheduling approach able to support manufacturing systems in different dynamic conditions. The negotiation protocol defined budget approach is based on a financial asset that each part obtains when it is released into the manufacturing system for processing. The part spends the budget to perform the manufacturing operations by the workstations; the virtual market in which part agent and workstation agents coordinate the decentralized system. A fuzzy tool is proposed to assign the budget to each part based on the objectives pursued. A simulation environment based on Rockwell ARENA® platform has been developed in order to test the proposed approach. The simulations are used to compare the proposed approach with classical dynamical scheduling approaches proposed in literature. The results show how the proposed approach leads to better results, and it can be selective among the different priority of the parts.


2011 ◽  
Vol 2-3 ◽  
pp. 608-613
Author(s):  
Ying Zi Wei ◽  
Yi Jun Feng ◽  
Kan Feng Gu

This paper builds an efficient agent-based flexible scheduling for real-world manufacturing systems. Considering the alternative processes and alternative machines, the allocation of manufacturing resources is achieved through negotiation among the job and machine agents in a multi-agent system (MAS). Ant Colony Intelligence (ACI) is proposed to be combined with Contract Net Protocol (CNP) so as to make agents adaptive to changing circumstances. ACI is integrated into both machine agents and job agents to solve the task allocation and sequencing problem. CNP is introduced to allow the agents to cooperate and coordinate their local schedules in order to find globally near-optimal robust schedules. The negotiation protocol is an interactive bidding mechanism based on the hybrid contract net protocol. The implementation of the issues using CNP model is discussed. Experimental results verify the effectiveness and efficiency of the proposed algorithm integrated with ant-inspired coordination.


2011 ◽  
Vol 383-390 ◽  
pp. 1555-1561
Author(s):  
Wu Li Wang ◽  
Yan Jiang Wang

In view of the characteristics of the oil drilling process and the existing problems of traditional simulation system, a new distributed drilling simulation model was established based on Multi-Agent system (MAS) technology. By means of autonomous, cooperative and reactive characteristic of Agent, the drilling laws and phenomenon can be reflected promptly and accurately under any circumstances. The MAS modeling for oil drilling simulation, the structure and knowledge representation of each Agent and the communication among Agents are described in detail. Finally, an Agent-based normal drilling well control simulation training example was given. The simulation results show that the simulator based on Multi-Agent system has better performances than traditional drilling simulators, and enhances the integrated training function of the drilling simulation system.


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