TY - GEN
T1 - Feasibility Cut Generation by Simulation
T2 - 2019 Winter Simulation Conference, WSC 2019
AU - Zhang, Mengyi
AU - Matta, Andrea
AU - Alfieri, Arianna
AU - Pedrielli, Giulia
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/12
Y1 - 2019/12
N2 - Simulation-optimization problems exhibit substantial inefficiencies when applied to high-dimensional problems. The problem is exacerbated in case where feasibility also needs to be evaluated using simulation. In this work, we propose an approximate iterative approach to identify feasible solutions and quickly find good solutions to the original problem. The approach is based on discrete event optimization (i.e., a mathematical programming representation of the simulation-optimization problems) and Benders decomposition, which is used for cut generation while a system alternative is simulated. The procedure is currently tailored for the server allocation problem in the multi-stage serial-parallel manufacturing line constrained to a target system time on a specific sample path. Results on randomly generated instances show its effectiveness in quickly eliminating infeasible solutions, thus decreasing the required computational effort and keeping the optimality gap low.
AB - Simulation-optimization problems exhibit substantial inefficiencies when applied to high-dimensional problems. The problem is exacerbated in case where feasibility also needs to be evaluated using simulation. In this work, we propose an approximate iterative approach to identify feasible solutions and quickly find good solutions to the original problem. The approach is based on discrete event optimization (i.e., a mathematical programming representation of the simulation-optimization problems) and Benders decomposition, which is used for cut generation while a system alternative is simulated. The procedure is currently tailored for the server allocation problem in the multi-stage serial-parallel manufacturing line constrained to a target system time on a specific sample path. Results on randomly generated instances show its effectiveness in quickly eliminating infeasible solutions, thus decreasing the required computational effort and keeping the optimality gap low.
UR - http://www.scopus.com/inward/record.url?scp=85081131470&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85081131470&partnerID=8YFLogxK
U2 - 10.1109/WSC40007.2019.9004762
DO - 10.1109/WSC40007.2019.9004762
M3 - Conference contribution
AN - SCOPUS:85081131470
T3 - Proceedings - Winter Simulation Conference
SP - 3633
EP - 3644
BT - 2019 Winter Simulation Conference, WSC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 8 December 2019 through 11 December 2019
ER -