Creating a flexible, simulation-based finite scheduling tool
Proceedings of the 29th conference on Winter simulation
Efficient simulation/optimization of dispatching priority with “fake” processing time
Proceedings of the 29th conference on Winter simulation
Implementing the theory of constraints philosophy in highly reentrant systems
Proceedings of the 30th conference on Winter simulation
Interating simulation based scheduling with MES in a semi-conductor fab
Proceedings of the 30th conference on Winter simulation
Proceedings of the 31st conference on Winter simulation: Simulation---a bridge to the future - Volume 1
Scheduling: Theory, Algorithms, and Systems
Scheduling: Theory, Algorithms, and Systems
Factory scheduling: simulation based scheduling using a two-pass approach
Proceedings of the 35th conference on Winter simulation: driving innovation
Factory scheduling: simulation-based finite scheduling at Albany International
Proceedings of the 35th conference on Winter simulation: driving innovation
Proceedings of the 38th conference on Winter simulation
Simulation-based multi-objective optimization of a real-world scheduling problem
Proceedings of the 38th conference on Winter simulation
A reflective context-aware system for spatial routing applications
Proceedings of the 6th international workshop on Middleware for pervasive and ad-hoc computing
Proceedings of the 40th Conference on Winter Simulation
A methodological approach to develop an integrated simulation system in manufacturing processes
ICOSSSE'07 Proceedings of the 6th WSEAS international conference on System science and simulation in engineering
Proceedings of the Winter Simulation Conference
Proceedings of the Winter Simulation Conference
Simulation based FAB scheduler: SeePlan®
Proceedings of the Winter Simulation Conference
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In semiconductor manufacturing, it requires more than one objective such as cycle time, machine utilization and due date accuracy to be kept in focus simultaneously, while developing an effective scheduling. In this paper, a near optimal solution, which is not inferior to any other feasible solutions in terms of all objectives, is generated with a combination of the analytically optimal and simulation based scheduling approach. First, the job shop scheduling problem is modeled using the discrete event simulation approach and the problem is divided in to simulation clock based lot selection sub-problems. Then, at each decision instant in simulated time, a Pareto optimal lot is selected using the various techniques to deal with multiobjective optimization such as weighted aggregation approach, global criterion method, minimum deviation method, and compromise programming. An illustration shows how these techniques work effectively in solving the multiobjective scheduling problem using discrete event simulation.