Comparison of weighting judgments in multiattribute utility measurement
Management Science
Simulation Budget Allocation for Further Enhancing theEfficiency of Ordinal Optimization
Discrete Event Dynamic Systems
Making Rational Decisions Using Adaptive Utility Elicitation
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
New Two-Stage and Sequential Procedures for Selecting the Best Simulated System
Operations Research
A POMDP formulation of preference elicitation problems
Eighteenth national conference on Artificial intelligence
Finding the best in the presence of a stochastic constraint
WSC '05 Proceedings of the 37th conference on Winter simulation
Application of multi-objective simulation-optimization techniques to inventory management problems
WSC '05 Proceedings of the 37th conference on Winter simulation
Ranking and selection with multiple "targets"
Proceedings of the 38th conference on Winter simulation
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
A Knowledge-Gradient Policy for Sequential Information Collection
SIAM Journal on Control and Optimization
A multi-objective selection procedure of determining a Pareto set
Computers and Operations Research
The knowledge-gradient stopping rule for ranking and selection
Proceedings of the 40th Conference on Winter Simulation
Economic Analysis of Simulation Selection Problems
Management Science
Bayesian Simulation and Decision Analysis: An Expository Survey
Decision Analysis
Sequential Sampling to Myopically Maximize the Expected Value of Information
INFORMS Journal on Computing
Stochastic Simulation Optimization: An Optimal Computing Budget Allocation
Stochastic Simulation Optimization: An Optimal Computing Budget Allocation
Entropy methods for adaptive utility elicitation
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
| Hi-index | 0.00 |
We consider an analyst tasked with using simulation to help a decision-maker choose among several decision alternatives. Each alternative has several competing attributes, e.g., cost and quality, that are unknown but can be estimated through simulation. We model this problem in a Bayesian context, where the decision-maker's preferences are described by a utility function, but this utility function is unknown to the analyst. The analyst must choose how to allocate his simulation budget among the alternatives in the face of uncertainty about both the alternatives' attributes, and the decision-maker's preferences. Only after simulation is complete are the decision-maker's preferences revealed. In this context, we calculate the value of the information in simulation samples, and propose a new multi-attribute ranking and selection procedure based on this value. This procedure is able to incorporate prior information about the decision-maker's preferences to improve sampling efficiency.