Novel multi-level optimization method for chemical complex using intelligent agent

Abstract

Multi-level optimization of complex chemical complex was comprehensively analyzed, including the optimization of management plan, production scheme, operating conditions, etc. The software framework of multi-level optimization of chemical complex was worked out. Basing upon the frame of multi-level optimization, the intelligent agent technique was adopted to search for global optimum. The organization, function, design and the implementation of a series of intelligent agents were discussed. According to the strategy that to spend most computing time in optimization solving and much less time in exchanging information regarding the tasks and results of optimization through network, the communication mechanism and cooperation rules for Multi-Agent System for hierarchically optimizing chemical complex was proposed.

Keywords

Intelligent Agent / chemical complex / multi-level optimization

References

[1] Davis R., Smith R. G.. Negotiation as metaphor for distributed problem solving. Artificial Intelligence, 1983, 20(1): 63-109.

[2] D’Inverno M., et al. Formalisms for multi-agent systems. The Knowledge Engineering Review, 1997, 12(3): 315-321.

[3] Grause M., Lewandowski A., Wierzbicki A.. Multi-objective decision analysis applied to chemical engineering. Computers & Chemical Engineering, 1984, 8(5): 285-293.

[4] Grossmann I.E.. Mixed-integer programming approach for the synthesis of integrated process flowsheets. Computers & Chemical Engineering, 1985, 9(5): 463.

[5] Papoulias S.A., Grossmann I.E.. A structural optimization approach in process synthesis-2: Heatrecovery networks. Computers & Chemical Engineering, 1983, 7(1): 707-721.

[6] Sahinidis N.V., Grossmann I.E., Fornari R.E., Chathrathi M.. Optimization model for long range planning in the chemical industry. Computers & Chemical Engineering, 1989, 13(1): 1049-1063.

[7] Soham Y.. Agent-oriented programming. Artificial Intelligence, 1993, 60(1): 51-92.

[8] Wooldridge M.. Intelligent agents: theory and practice. The Knowledge Engineering Review, 1995, 10(2): 115-152.

[9] Zhang N., Zhu X.X.. A novel modeling and decomposition strategy for overall refinery optimization. Computers & Chemical Engineering, 2000, 24(2): 1543-1548.