A simulation based cut generation approach to improve deo efficiency: The buffer allocation case

Mengyi Zhang, Andrea Matta, Arianna Alfieri, Giulia Pedrielli

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The stochastic Buffer Allocation Problem (BAP) is well known in several fields and it has been characterized as NP-Hard. It deals with the optimal allocation of buffer spaces among stages of a system. Simulation Optimization is a possible way to approximately solve the problem. In particular, we refer to the Discrete Event Optimization (DEO). According to this approach, BAP simulation optimization can be modeled as a Mixed Integer Programming model. Despite the advantages deriving from having a single model for both simulation and optimization, its solution can be extremely demanding. In this work, we propose a Benders decomposition approach to efficiently solve large DEO of BAP, in which cuts are generated by simulation. Numerical experiment shows that the computation time can be significantly reduced by using this approach. Pedrielli, Matta, and Alfieri (2015) proposed a general DEO framework to model and optimize queueing systems. The approach relies on the Event Relationship Graph Lite (ERG Lite) formalism to formulate integrated simulation optimization mathematical programming models. ERG Lite is an extension of the Event Relationship Graphs. The authors showed that the BAP can be solved by DEO (Matta 2008) models that contain both simulation and optimization aspects. The simulation components control the event times, by means of constraints dealing with the system dynamics. The optimization components, instead, correspond to the binary variables and related constraints used for the capacity selection and minimization of total buffer space.

Original languageEnglish (US)
Title of host publication2016 Winter Simulation Conference
Subtitle of host publicationSimulating Complex Service Systems, WSC 2016
EditorsTheresa M. Roeder, Peter I. Frazier, Robert Szechtman, Enlu Zhou
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3710-3711
Number of pages2
ISBN (Electronic)9781509044863
DOIs
StatePublished - Jul 2 2016
Event2016 Winter Simulation Conference, WSC 2016 - Arlington, United States
Duration: Dec 11 2016Dec 14 2016

Publication series

NameProceedings - Winter Simulation Conference
Volume0
ISSN (Print)0891-7736

Other

Other2016 Winter Simulation Conference, WSC 2016
CountryUnited States
CityArlington
Period12/11/1612/14/16

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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    Zhang, M., Matta, A., Alfieri, A., & Pedrielli, G. (2016). A simulation based cut generation approach to improve deo efficiency: The buffer allocation case. In T. M. Roeder, P. I. Frazier, R. Szechtman, & E. Zhou (Eds.), 2016 Winter Simulation Conference: Simulating Complex Service Systems, WSC 2016 (pp. 3710-3711). [7822412] (Proceedings - Winter Simulation Conference; Vol. 0). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/WSC.2016.7822412