Simulation modeling with event graphs
Communications of the ACM
Mathematical programming models of discrete event system dynamics
Proceedings of the 32nd conference on Winter simulation
Graphical Simulation Modeling and Analysis: Using SIGMA for Windows
Graphical Simulation Modeling and Analysis: Using SIGMA for Windows
Proceedings of the 35th conference on Winter simulation: driving innovation
An event graph based simulation and scheduling analysis of multi-cluster tools
WSC '04 Proceedings of the 36th conference on Winter simulation
A queuing network model for the management of berth crane operations
Computers and Operations Research
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In most scheduling literature, constraints are seemingly generated in an ad-hoc manner using intuitive arguments. This could result in overlooking some constraints or including unnecessary constraints. Schruben (2000) has shown how the dynamics of some discrete event systems can be modeled as the solutions of optimization programs. In this paper, we use this idea to generate mathematical programming models systematically for scheduling resources in discrete event dynamic systems. Two examples are presented: a multiple server queue and a semiconductor manufacturing cluster tool. An interesting result was that the mathematical structure of the scheduling program generated from a simulation of a cluster tool found in the literature leads to a different, more concise and illuminating cluster tool simulation model that would have been difficult to discover otherwise. The corresponding optimal scheduling problem is surprising in that it does not include explicit representation of the resource that is actually being scheduled!