A branch and bound algorithm for the job-shop scheduling problem
Discrete Applied Mathematics - Special volume: viewpoints on optimization
Fuzzy arithmetic with requisite constraints
Fuzzy Sets and Systems - Special issue: fuzzy arithmetic
A review on evolution of production scheduling with neural networks
Computers and Industrial Engineering
Adaptive fuzzy control of a non-linear servo-drive: Theory and experimental results
Engineering Applications of Artificial Intelligence
Fuzzy production control with limited resources and response delay
Computers and Industrial Engineering
Distributed control of production systems
Engineering Applications of Artificial Intelligence
Intelligent distributed and supervised flow control methodology for production systems
Engineering Applications of Artificial Intelligence
Development of genetic fuzzy logic controllers for complex production systems
Computers and Industrial Engineering
Optimisation criteria in development of fuzzy controllers with dynamics
Engineering Applications of Artificial Intelligence
On stability of fuzzy systems expressed by fuzzy rules with singleton consequents
IEEE Transactions on Fuzzy Systems
Robust stability constraints for fuzzy model predictive control
IEEE Transactions on Fuzzy Systems
Inverse controller design for fuzzy interval systems
IEEE Transactions on Fuzzy Systems
MIN and MAX Operators for Fuzzy Intervals and Their Potential Use in Aggregation Operators
IEEE Transactions on Fuzzy Systems
Brief Paper: Real-time control of manufacturing cells using dynamic neural networks
Automatica (Journal of IFAC)
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This paper considers the design and the practical implementation of a stable multiple objective real-time scheduling problem for a complex production system. In this paper, a complex production system is viewed as a kind of systems producing a variety of products (multiple-part-type) under constraints and multiple production objectives often conflicting. Previously, fuzzy control theory and fuzzy intervals arithmetic have been used to develop a distributed and supervised continuous-flow control architecture. In this framework, the objective of the distributed control structure is to balance the production process by adjusting the continuous production rates of the machines on the basis of the average local behavior. The supervisory control methodology aims at maintaining the overall performances within acceptable limits. In the new proposed approach, the problem of a stable real-time scheduling of jobs is considered at the shop-floor level. In this context, as the stability of the control structure is ensured, the actual dispatching times are determined from the continuous production rates through a discretization procedure. To deal with conflicts between jobs at a shared machine, a decision is made. It concerns the actual part to be processed and uses some criterions representing a measure of the job's priority. The simulation results show the validity of the proposed approach in terms of production cost, robustness and system stability.