Automatically generated object-oriented genetic programs to optimize adaptive job shop control and scheduling system.

摘要

The requirements for Production Planning and Control (PPu26C) System have fundamentally changed during last years. The increasingly complex production processes and constantly changing production environment require the system able to be agile, flexible and adaptable to the changing situations from markets, customers, new technology, environment, and so on. Fraunhofer Institute of Production and Automation (IPA), Stuttgart. Germany created an experimentation environment of software agent, event-oriented simulation and evolutionary strategies, to examine adaptive approach for the PPu26C system. The project of Agent Learning Adaptive Network (ALAN), Fraunhofer---IPA proposed, focused on the Job Shop Control level to explore the new order management paradigm applicable to small and medium sized enterprises (SMEs). Object-oriented programs automatically generated by Genetic Programming are expected to automatically co-ordinate between multiple intelligent agents to reach systemu27s global targets. This research extends genetic programming beyond its current generation of functional and procedural programs to the generation of object-oriented programs. Successful achievement of this goal will represent a significant advance in the practice of genetic programming in Object-Orientation. Paper copy at Leddy Library: Theses u26 Major Papers - Basement, West Bldg. / Call Number: Thesis2001 .Y83. Source: Masters Abstracts International, Volume: 40-06, page: 1561. Adviser: Arunita Jaekel. Thesis (M.Sc.)--University of Windsor (Canada), 2001.