Communicating sequential processes
Communicating sequential processes
Theory of linear and integer programming
Theory of linear and integer programming
The shifting bottleneck procedure for job shop scheduling
Management Science
Operating system concepts (3rd ed.)
Operating system concepts (3rd ed.)
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Modeling and verification of randomized distributed real-time systems
Modeling and verification of randomized distributed real-time systems
A fast taboo search algorithm for the job shop problem
Management Science
Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory
Genetic Algorithms: Principles and Perspectives: A Guide to GA Theory
Compositional Synthesis of Maximally Permissive Supervisors Using Supervision Equivalence
Discrete Event Dynamic Systems
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Automation and flexibility are often mentioned as key concepts in modern production industry. To increase the level of flexibility, deterministic finite automata (DFA) can be used to model, specify and verify the production systems. Often, it is also desirable to optimize some production criteria, such as for example the cycle time of a manufacturing cell. In this paper, a method for automatic conversion from DFA to a mixed integer linear programming (MILP) formulation is first presented. This conversion is developed for a number of DFA structures that have shown to be useful in practical applications. Special attention is paid to reducing the search region explored by the MILP solver. Second, a conversion from the MILP solution to a DFA supervisor is described. This allows to combine the advantages of DFA modeling with the efficiency of MILP and supervisory control theory to automatically generate time-optimal, collision-free and non-blocking working schedules for flexible manufacturing systems.