Semi-global stabilization of discrete-time linear systems with position and rate-limited actuators
Systems & Control Letters
The New Science of Management Decision
The New Science of Management Decision
Decision Support Systems and Intelligent Systems
Decision Support Systems and Intelligent Systems
Distributed Manufacturing Scheduling Using Intelligent Agents
IEEE Intelligent Systems
Optimal Negotiation Strategies for Agents with Incomplete Information
ATAL '01 Revised Papers from the 8th International Workshop on Intelligent Agents VIII
Negotiation in multi-agent systems
The Knowledge Engineering Review
Agent-based decision support system for dynamic scheduling of a flexible manufacturing system
International Journal of Computer Applications in Technology
Negotiation Process for Multi-Agent DSS for Manufacturing System
Proceedings of the 2008 conference on Collaborative Decision Making: Perspectives and Challenges
Multiagent approach for the representation of information in a decision support system
AIMSA'06 Proceedings of the 12th international conference on Artificial Intelligence: methodology, Systems, and Applications
Proceedings of the 2010 conference on Bridging the Socio-technical Gap in Decision Support Systems: Challenges for the Next Decade
Web-based multi-agent system architecture in a dynamic environment
International Journal of Knowledge-based and Intelligent Engineering Systems
Intelligent Decision Technologies
A holonic approach to flexible flow shop scheduling under stochastic processing times
Computers and Operations Research
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For decision support systems, the software agents' integration provides an automated, cost-effective means for making decisions. The agents in the system autonomously plan and pursue their actions and sub-goals to cooperate, coordinate, and negotiate with others, and to respond flexibly and intelligently to dynamic and unpredictable situations. In real time production management, the DSS memorizes the current state of the workshop. It knows constantly all possible decisions and the possible events involved. We distinguish 3 contexts for the decision-making aid: (1) Decision-making aid in the context of an acceptable sequence; (2) Assistance for the admissibility covering; and (3) negotiation support among different decision-making centers in a dynamic context. The present paper proposes an agent architecture-based DSS in order to solve some uncertainty problems in dynamic production system scheduling. The proposed DSS gives the decision centers the opportunity to make decisions in a dynamical context. Specifically, Integrated Station of Production agents will be equipped with a sufficient behavior to carry out practical operations and simultaneously react to the complex problems caused by the dynamic scheduling in real situations. These atents express their preferences by using ELECTRE III method in order to solve differences. The negotiation mechanism is based on the well-known Contract Net Protocol. The approach is tested through simple scenarios.