Abstract
Large solution space is one of the main features of simulation-optimization problems. Reducing the cardinality of the set of alternatives is a key point for increasing the efficiency of simulation-optimization methods. In this work, a new cutting approach is proposed for this purpose. The approach exploits the Benders Decomposition framework that can be effectively applied when the simulation-optimization problems are represented using Discrete Event Optimization models. Benders Decomposition subproblems represent the simulation components, hence, cuts can be easily generated observing the values of the variables while a system alternative is simulated, without solving any subproblem. The cut generation procedure is proposed to approximately solve the Server Allocation Problem in a tandem queueing system. Results on randomly generated instances show its effectiveness in decreasing the computational effort by reducing the solution space.
| Original language | English (US) |
|---|---|
| Title of host publication | WSC 2018 - 2018 Winter Simulation Conference |
| Subtitle of host publication | Simulation for a Noble Cause |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 2225-2236 |
| Number of pages | 12 |
| ISBN (Electronic) | 9781538665725 |
| DOIs | |
| State | Published - Jan 31 2019 |
| Event | 2018 Winter Simulation Conference, WSC 2018 - Gothenburg, Sweden Duration: Dec 9 2018 → Dec 12 2018 |
Publication series
| Name | Proceedings - Winter Simulation Conference |
|---|---|
| Volume | 2018-December |
| ISSN (Print) | 0891-7736 |
Conference
| Conference | 2018 Winter Simulation Conference, WSC 2018 |
|---|---|
| Country | Sweden |
| City | Gothenburg |
| Period | 12/9/18 → 12/12/18 |
Fingerprint
ASJC Scopus subject areas
- Software
- Modeling and Simulation
- Computer Science Applications
Cite this
Simulation-based Benders cuts : A new cutting approach to approximately solve simulation-optimization problems. / Zhang, Mengyi; Matta, Andrea; Alfieri, Arianna; Pedrielli, Giulia.
WSC 2018 - 2018 Winter Simulation Conference: Simulation for a Noble Cause. Institute of Electrical and Electronics Engineers Inc., 2019. p. 2225-2236 8632326 (Proceedings - Winter Simulation Conference; Vol. 2018-December).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Simulation-based Benders cuts
T2 - A new cutting approach to approximately solve simulation-optimization problems
AU - Zhang, Mengyi
AU - Matta, Andrea
AU - Alfieri, Arianna
AU - Pedrielli, Giulia
PY - 2019/1/31
Y1 - 2019/1/31
N2 - Large solution space is one of the main features of simulation-optimization problems. Reducing the cardinality of the set of alternatives is a key point for increasing the efficiency of simulation-optimization methods. In this work, a new cutting approach is proposed for this purpose. The approach exploits the Benders Decomposition framework that can be effectively applied when the simulation-optimization problems are represented using Discrete Event Optimization models. Benders Decomposition subproblems represent the simulation components, hence, cuts can be easily generated observing the values of the variables while a system alternative is simulated, without solving any subproblem. The cut generation procedure is proposed to approximately solve the Server Allocation Problem in a tandem queueing system. Results on randomly generated instances show its effectiveness in decreasing the computational effort by reducing the solution space.
AB - Large solution space is one of the main features of simulation-optimization problems. Reducing the cardinality of the set of alternatives is a key point for increasing the efficiency of simulation-optimization methods. In this work, a new cutting approach is proposed for this purpose. The approach exploits the Benders Decomposition framework that can be effectively applied when the simulation-optimization problems are represented using Discrete Event Optimization models. Benders Decomposition subproblems represent the simulation components, hence, cuts can be easily generated observing the values of the variables while a system alternative is simulated, without solving any subproblem. The cut generation procedure is proposed to approximately solve the Server Allocation Problem in a tandem queueing system. Results on randomly generated instances show its effectiveness in decreasing the computational effort by reducing the solution space.
UR - http://www.scopus.com/inward/record.url?scp=85062621891&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85062621891&partnerID=8YFLogxK
U2 - 10.1109/WSC.2018.8632326
DO - 10.1109/WSC.2018.8632326
M3 - Conference contribution
AN - SCOPUS:85062621891
T3 - Proceedings - Winter Simulation Conference
SP - 2225
EP - 2236
BT - WSC 2018 - 2018 Winter Simulation Conference
PB - Institute of Electrical and Electronics Engineers Inc.
ER -