Optimized fuzzy scheduling of manufacturing systems
نویسندگان
چکیده
An Evolutionary Algorithm (EA) strategy for the optimization of generic Work-In-Process (WIP) scheduling fuzzy controllers is presented. The EA is used to tune a set of fuzzy control modules which are used for distributed and supervisory WIP scheduling. The distributed controllers objective is to control the rate in each production stage so that satisfies the demand for final products while reducing WIP within the system. The EA identifies the parameters for which the fuzzy controller performs optimal with respect to WIP and backlog minimization. The proposed strategy is compared to known heuristically tuned fuzzy control approaches. Simulation results show that the EA strategy improves system’s performance.
منابع مشابه
MULTI-OBJECTIVE ROUTING AND SCHEDULING IN FLEXIBLE MANUFACTURING SYSTEMS UNDER UNCERTAINTY
The efficiency of transportation system management plays an important role in the planning and operation efficiency of flexible manufacturing systems. Automated Guided Vehicles (AGV) are part of diversified and advanced techniques in the field of material transportation which have many applications today and act as an intermediary between operating and storage equipment and are routed and contr...
متن کاملScheduling of Flexible Manufacturing Systems using Fuzzy Logic: A Review
The task of scheduling in flexible manufacturing systems (FMS) is more complex and problematic than a traditional manufacturing systems. To accomplish great performance for FMS, a good scheduling system should make an accurate decision at an accurate time according to system situations. Fuzzy logic methodologies easily deal with indeterminate and incomplete information. Human expert‟s knowledge...
متن کاملTwo-stage fuzzy-stochastic programming for parallel machine scheduling problem with machine deterioration and operator learning effect
This paper deals with the determination of machine numbers and production schedules in manufacturing environments. In this line, a two-stage fuzzy stochastic programming model is discussed with fuzzy processing times where both deterioration and learning effects are evaluated simultaneously. The first stage focuses on the type and number of machines in order to minimize the total costs associat...
متن کاملScheduling of flexible manufacturing systems using genetic algorithm: A heuristic approach
Scheduling of production in Flexible Manufacturing Systems (FMSs) has been extensively investigated over the past years and it continues to attract the interest of both academic researchers and practitioners. The generation of new and modified production schedules is becoming a necessity in today’s complex manufacturing environment. Genetic algorithms are used in this paper to obtain an initial...
متن کاملA modified branch and bound algorithm for a vague flow-shop scheduling problem
Uncertainty plays a significant role in modeling and optimization of real world systems. Among uncertain approaches, fuzziness describes impreciseness while for ambiguity another definition is required. Vagueness is a probabilistic model of uncertainty being helpful to include ambiguity into modeling different processes especially in industrial systems. In this paper, a vague set based on dista...
متن کامل