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Simulation-Based Optimization Using Greedy Techniques and Simulated Annealing for Optimal Equipment Selection Within Print Production Environments

Sudhendu Rai (), Eric Gross () and Ranjit Kumar Ettam ()
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Sudhendu Rai: Xerox Corporation
Eric Gross: Xerox Corporation
Ranjit Kumar Ettam: Xerox Corporation

A chapter in Applied Simulation and Optimization, 2015, pp 277-301 from Springer

Abstract: Abstract Xerox has invented, tested, and implemented a novel class of operations-research-based productivity improvement offerings, marketed as Lean Document Production (LDP), for the $100 billion printing industry in the United States. The software toolkit that enables the optimization of print shops is data-driven and simulation-based. It enables quick modeling of complex print production environments under the cellular production framework. The software toolkit automates several steps of the modeling process by taking declarative inputs from the end user and then automatically generating complex simulation models that are used to determine improved design and operating policies. This chapter describes the addition of another layer of automation consisting of simulation-based optimization using simulated annealing and greedy search techniques that enable the search of a large number of design alternatives in the presence of operational and cost constraints. The greedy search procedure quickly determines an acceptable solution in a web-based online application environment. The simulated annealing technique is more time consuming and is performed offline. The results of the application of this approach to real-world problems are described.

Keywords: Simulated Annealing; Greedy Algorithm; Turnaround Time; Simulated Annealing Algorithm; Simulated Annealing Approach (search for similar items in EconPapers)
Date: 2015
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-15033-8_9

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DOI: 10.1007/978-3-319-15033-8_9

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