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P robably one of the most successful interfaces between operations research and computer science has been the development of discrete-event simulation software. The recent integration of optimization techniques into simulation practice, specifically into commercial software, has become nearly ubiquitous, as most discrete-event simulation packages now… (More)

- Jiaqiao Hu, Michael C. Fu, Steven I. Marcus
- Operations Research
- 2007

We introduce a new randomized method called Model Reference Adaptive Search (MRAS) for solving global optimization problems. The method works with a parameterized probabilistic model on the solution space and generates at each iteration a group of candidate solutions. These candidate solutions are then used to update the parameters associated with the… (More)

- Chun-Hung Chen, Donghai He, Michael C. Fu, Loo Hay Lee
- INFORMS Journal on Computing
- 2008

We consider a variation of the subset selection problem in ranking and selection, where motivated by recently developed global optimization approaches applied to simulation optimization, our objective is to identify the top-m out of k designs based on simulated output. Using the optimal computing budget framework, we formulate the problem as that of… (More)

- Shalabh Bhatnagar, Michael C. Fu, Steven I. Marcus, I-Jeng Wang
- ACM Trans. Model. Comput. Simul.
- 2003

Simultaneous perturbation stochastic approximation (SPSA) algorithms have been found to be very effective for high-dimensional simulation optimization problems. The main idea is to estimate the gradient using simulation output performance measures at only <i>two</i> settings of the <i>N</i>-dimensional parameter vector being optimized rather than at the… (More)

- Michael C. Fu
- Operations Research
- 1994

Monte Carlo simulation is one alternative for analyzing options markets when the assumptions of simpler analytical models are violated. We introduce techniques for the sensitivity analysis of option pricing which can be efficiently carried out in the simulation. In particular, using these techniques, a single run of the simulation would often provide not… (More)

- Sridhar Bashyam, KPMG Peat Marwick, Michael C. Fu
- 1997

A major assumption in the analysis of (s; S) inventory systems with stochastic lead times is that orders are received in the same sequence as they are placed. Even under this assumption, much of the work to date has focused on the unconstrained optimization of the system, in which a penalty cost for unsatissed demand is assigned. The literature on… (More)

- Ying He, Michael C. Fu, Steven I. Marcus
- IEEE Trans. Automat. Contr.
- 2003

In this paper, we consider Simultaneous Perturbation Stochastic Approximation (SPSA) for function minimization. The standard assumption for convergence is that the function be three times differentiable, although weaker assumptions have been used for special cases. However, all work that we are aware of at least requires differentiability. In this paper, we… (More)

A number of Monte Carlo simulation-based approaches have been proposed within the past decade to address the problem of pricing American-style derivatives. The purpose of this paper is to empirically test some of these algorithms on a common set of problems in order to be able to assess the strengths and weaknesses of each approach as a function of the… (More)

- Hyeong Soo Chang, Michael C. Fu, Jiaqiao Hu, Steven I. Marcus
- Operations Research
- 2005

Based on recent results for multiarmed bandit problems, we propose an adaptive sampling algorithm that approximates the optimal value of a finite-horizon Markov decision process (MDP) with finite state and action spaces. The algorithm adaptively chooses which action to sample as the sampling process proceeds and generates an asymptotically unbiased… (More)