Experiments in quadratic 0-1 programming
Mathematical Programming: Series A and B
A fully sequential procedure for indifference-zone selection in simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Simulation Budget Allocation for Further Enhancing theEfficiency of Ordinal Optimization
Discrete Event Dynamic Systems
Ranking and Selection for Steady-State Simulation: Procedures and Perspectives
INFORMS Journal on Computing
Using Ranking and Selection to "Clean Up" after Simulation Optimization
Operations Research
Simulation optimization with countably infinite feasible regions: Efficiency and convergence
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Simulation Modeling and Analysis with Expertfit Software
Simulation Modeling and Analysis with Expertfit Software
Discrete Optimization via Simulation Using COMPASS
Operations Research
Simulation of Coherent Risk Measures Based on Generalized Scenarios
Management Science
Selecting a Selection Procedure
Management Science
Balanced Explorative and Exploitative Search with Estimation for Simulation Optimization
INFORMS Journal on Computing
Industrial strength COMPASS: A comprehensive algorithm and software for optimization via simulation
ACM Transactions on Modeling and Computer Simulation (TOMACS)
Sequential Sampling to Myopically Maximize the Expected Value of Information
INFORMS Journal on Computing
Optimal Allocation of Surgery Blocks to Operating Rooms Under Uncertainty
Operations Research
A brief introduction to optimization via simulation
Winter Simulation Conference
An Adaptive Hyperbox Algorithm for High-Dimensional Discrete Optimization via Simulation Problems
INFORMS Journal on Computing
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Some existing simulation optimization algorithms e.g., adaptive random search become pure random search methods and thus are ineffective for the zero-one optimization via simulation problem. In this paper, we present highly efficient rapid screening procedures for solving the zero-one optimization via simulation problem. Three approaches adopting different sampling rules and providing different statistical guarantees are described. We also propose efficient neighborhood search methods and a simple algorithm for generation of initial solutions, all of which can be incorporated into our rapid screening procedures. The proposed procedures are more adaptive than ordinary ranking and selection procedures because in each iteration they can eliminate inferior solutions and intelligently sample promising solutions from the neighborhood of the survivors. Empirical studies are performed to compare the efficiency of the proposed procedures with other existing ones.