Handbook of Scheduling: Algorithms, Models, and Performance Analysis
Handbook of Scheduling: Algorithms, Models, and Performance Analysis
An adaptive solution to dynamic transport optimization
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Metaheuristic Optimization via Memory and Evolution: Tabu Search and Scatter Search (Operations Research/Computer Science Interfaces Series)
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Magenta technology multi-agent logistics i-Scheduler for road transportation
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
MagentaToolkit: A Set of Multi-agent Tools for Developing Adaptive Real-Time Applications
HoloMAS '07 Proceedings of the 3rd international conference on Industrial Applications of Holonic and Multi-Agent Systems: Holonic and Multi-Agent Systems for Manufacturing
HoloMAS'11 Proceedings of the 5th international conference on Industrial applications of holonic and multi-agent systems for manufacturing
HoloMAS'11 Proceedings of the 5th international conference on Industrial applications of holonic and multi-agent systems for manufacturing
Hierarchical multi-agent distribution planning
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
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The paper gives overview of a multi-agent real-time scheduler for the European operation of one of the largest rent-a-car company in the world. It describes requirements for scheduling of cars and drivers and outlines main features of the ontology-based, multi-agent approach, including systems architecture and performance measurements. The key design decisions and results of the first stage of the system development are also covered. The system is capable of scheduling complex interdependent operations of a large number of resources and of updating schedules affected by the occurrence of unpredictable events in real time. The multi-agent approach developed for scheduling of car rentals can be applied to a variety of complex real-time scheduling and optimization applications.