A mathematical programming approach to a deterministic Kanban system
Management Science
Kanban controlled pull systems: an analytic approach
Management Science
Estimating simulation metamodel parameters for unexpected shop floor real time events
Proceedings of the 12th annual conference on Computers and industrial engineering
Computers and Operations Research
Simulation optimization using simulated annealing
Computers and Industrial Engineering
The determination of the optimal number of kanbans in a Just-In-Time production system
Computers and Industrial Engineering
Metamodels for simulation input-output relations
WSC '92 Proceedings of the 24th conference on Winter simulation
Comparison of global search methods for design optimization using simulation
WSC '91 Proceedings of the 23rd conference on Winter simulation
WSC '88 Proceedings of the 20th conference on Winter simulation
A survey on metaheuristics for stochastic combinatorial optimization
Natural Computing: an international journal
Hybrid search algorithm to optimize scheduling problems for TCPN models
Proceedings of the 2010 Summer Computer Simulation Conference
Investigating the use of multi meta-heuristics in simulation optimization
Proceedings of the Winter Simulation Conference
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Investigation of the performance and operation of complex systems in manufacturing or other environments, analytical models of these systems become very complicated. Because of the complex stochastic characteristic of the systems, simulation is used as a tool to analyze them. The trust of such simulation analysis usually is to determine the optimum combination of factors that effect the considered system performance. The purpose of this study is to use a tabu search algorithm in conjunction with a simulation model of a JIT system to find the optimum number of kanbans.