A simulation-based benders' cuts generation for the joint workstation, workload and buffer allocation problem

Mengyi Zhang, Andrea Matta, Arianna Alfieri, Giulia Pedrielli

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

Abstract

The Discrete Event Optimization (DEO) framework was recently proposed to formulate the simulation-optimization model of the Joint Workstation, Workload and Buffer Allocation Problem (JWWBAP) of the open flow line. However, the computational effort to solve the DEO model at optimality is quite high, because it is a mixed integer linear programming model. This work proposes a simulation cutting approach to efficiently solve the DEO model of the JWWBAP. Specifically, the DEO model is decomposed into an optimization model and a simulation model, which are the master problem and the subproblem in Benders decomposition, respectively. The optimization model is solved to find a system configuration, and the simulation model is solved to add cuts to the optimization model. An algorithm is proposed to generate cut using the simulation trajectory. Numerical analysis shows that the exact DEO model can be solved efficiently.

Original languageEnglish (US)
Title of host publication2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017
PublisherIEEE Computer Society
Pages1067-1072
Number of pages6
Volume2017-August
ISBN (Electronic)9781509067800
DOIs
StatePublished - Jan 12 2018
Event13th IEEE Conference on Automation Science and Engineering, CASE 2017 - Xi'an, China
Duration: Aug 20 2017Aug 23 2017

Other

Other13th IEEE Conference on Automation Science and Engineering, CASE 2017
CountryChina
CityXi'an
Period8/20/178/23/17

Fingerprint

Linear programming
Numerical analysis
Trajectories
Decomposition

Keywords

  • buffer allocation problem
  • decomposition
  • manufacturing system
  • mathematical programming

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

Cite this

Zhang, M., Matta, A., Alfieri, A., & Pedrielli, G. (2018). A simulation-based benders' cuts generation for the joint workstation, workload and buffer allocation problem. In 2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017 (Vol. 2017-August, pp. 1067-1072). IEEE Computer Society. https://doi.org/10.1109/COASE.2017.8256247

A simulation-based benders' cuts generation for the joint workstation, workload and buffer allocation problem. / Zhang, Mengyi; Matta, Andrea; Alfieri, Arianna; Pedrielli, Giulia.

2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017. Vol. 2017-August IEEE Computer Society, 2018. p. 1067-1072.

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

Zhang, M, Matta, A, Alfieri, A & Pedrielli, G 2018, A simulation-based benders' cuts generation for the joint workstation, workload and buffer allocation problem. in 2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017. vol. 2017-August, IEEE Computer Society, pp. 1067-1072, 13th IEEE Conference on Automation Science and Engineering, CASE 2017, Xi'an, China, 8/20/17. https://doi.org/10.1109/COASE.2017.8256247
Zhang M, Matta A, Alfieri A, Pedrielli G. A simulation-based benders' cuts generation for the joint workstation, workload and buffer allocation problem. In 2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017. Vol. 2017-August. IEEE Computer Society. 2018. p. 1067-1072 https://doi.org/10.1109/COASE.2017.8256247
Zhang, Mengyi ; Matta, Andrea ; Alfieri, Arianna ; Pedrielli, Giulia. / A simulation-based benders' cuts generation for the joint workstation, workload and buffer allocation problem. 2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017. Vol. 2017-August IEEE Computer Society, 2018. pp. 1067-1072
@inproceedings{cc25b7dc1222476bb863800f42e717d1,
title = "A simulation-based benders' cuts generation for the joint workstation, workload and buffer allocation problem",
abstract = "The Discrete Event Optimization (DEO) framework was recently proposed to formulate the simulation-optimization model of the Joint Workstation, Workload and Buffer Allocation Problem (JWWBAP) of the open flow line. However, the computational effort to solve the DEO model at optimality is quite high, because it is a mixed integer linear programming model. This work proposes a simulation cutting approach to efficiently solve the DEO model of the JWWBAP. Specifically, the DEO model is decomposed into an optimization model and a simulation model, which are the master problem and the subproblem in Benders decomposition, respectively. The optimization model is solved to find a system configuration, and the simulation model is solved to add cuts to the optimization model. An algorithm is proposed to generate cut using the simulation trajectory. Numerical analysis shows that the exact DEO model can be solved efficiently.",
keywords = "buffer allocation problem, decomposition, manufacturing system, mathematical programming",
author = "Mengyi Zhang and Andrea Matta and Arianna Alfieri and Giulia Pedrielli",
year = "2018",
month = "1",
day = "12",
doi = "10.1109/COASE.2017.8256247",
language = "English (US)",
volume = "2017-August",
pages = "1067--1072",
booktitle = "2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017",
publisher = "IEEE Computer Society",

}

TY - GEN

T1 - A simulation-based benders' cuts generation for the joint workstation, workload and buffer allocation problem

AU - Zhang, Mengyi

AU - Matta, Andrea

AU - Alfieri, Arianna

AU - Pedrielli, Giulia

PY - 2018/1/12

Y1 - 2018/1/12

N2 - The Discrete Event Optimization (DEO) framework was recently proposed to formulate the simulation-optimization model of the Joint Workstation, Workload and Buffer Allocation Problem (JWWBAP) of the open flow line. However, the computational effort to solve the DEO model at optimality is quite high, because it is a mixed integer linear programming model. This work proposes a simulation cutting approach to efficiently solve the DEO model of the JWWBAP. Specifically, the DEO model is decomposed into an optimization model and a simulation model, which are the master problem and the subproblem in Benders decomposition, respectively. The optimization model is solved to find a system configuration, and the simulation model is solved to add cuts to the optimization model. An algorithm is proposed to generate cut using the simulation trajectory. Numerical analysis shows that the exact DEO model can be solved efficiently.

AB - The Discrete Event Optimization (DEO) framework was recently proposed to formulate the simulation-optimization model of the Joint Workstation, Workload and Buffer Allocation Problem (JWWBAP) of the open flow line. However, the computational effort to solve the DEO model at optimality is quite high, because it is a mixed integer linear programming model. This work proposes a simulation cutting approach to efficiently solve the DEO model of the JWWBAP. Specifically, the DEO model is decomposed into an optimization model and a simulation model, which are the master problem and the subproblem in Benders decomposition, respectively. The optimization model is solved to find a system configuration, and the simulation model is solved to add cuts to the optimization model. An algorithm is proposed to generate cut using the simulation trajectory. Numerical analysis shows that the exact DEO model can be solved efficiently.

KW - buffer allocation problem

KW - decomposition

KW - manufacturing system

KW - mathematical programming

UR - http://www.scopus.com/inward/record.url?scp=85044968611&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85044968611&partnerID=8YFLogxK

U2 - 10.1109/COASE.2017.8256247

DO - 10.1109/COASE.2017.8256247

M3 - Conference contribution

VL - 2017-August

SP - 1067

EP - 1072

BT - 2017 13th IEEE Conference on Automation Science and Engineering, CASE 2017

PB - IEEE Computer Society

ER -