TY - GEN

T1 - Using Simulation to Approximate the Minimum Cost of a Finite Set of Alternatives

AU - Zheng, Cuicui

AU - Calvin, James

N1 - Funding Information:
This work was supported by the National Science Foundation under Grant No. CMMI-1562466.
Publisher Copyright:
© 2019 IEEE.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2019/12

Y1 - 2019/12

N2 - We consider the problem of approximating the minimum cost of a finite set of alternative systems. We can not directly observe the cost of the systems, but we can estimate the cost using simulation. The simulation run lengths are adaptively chosen for each system. We describe an optimization algorithm and establish a bound on the error convergence rate. Compared with a single system, the error grows by an additional factor of the square root of the logarithm of the number of systems and the simulation budget.

AB - We consider the problem of approximating the minimum cost of a finite set of alternative systems. We can not directly observe the cost of the systems, but we can estimate the cost using simulation. The simulation run lengths are adaptively chosen for each system. We describe an optimization algorithm and establish a bound on the error convergence rate. Compared with a single system, the error grows by an additional factor of the square root of the logarithm of the number of systems and the simulation budget.

UR - http://www.scopus.com/inward/record.url?scp=85081132095&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85081132095&partnerID=8YFLogxK

U2 - 10.1109/WSC40007.2019.9004840

DO - 10.1109/WSC40007.2019.9004840

M3 - Conference contribution

AN - SCOPUS:85081132095

T3 - Proceedings - Winter Simulation Conference

SP - 3428

EP - 3435

BT - 2019 Winter Simulation Conference, WSC 2019

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2019 Winter Simulation Conference, WSC 2019

Y2 - 8 December 2019 through 11 December 2019

ER -