Panel: simulation optimization: future of simulation optimization
Proceedings of the 33nd conference on Winter simulation
Genetic Algorithms for Multiobjective Optimization: FormulationDiscussion and Generalization
Proceedings of the 5th International Conference on Genetic Algorithms
Pin: building customized program analysis tools with dynamic instrumentation
Proceedings of the 2005 ACM SIGPLAN conference on Programming language design and implementation
New advances and applications for marrying simulation and optimization
WSC '04 Proceedings of the 36th conference on Winter simulation
Simulation optimization: a review, new developments, and applications
WSC '05 Proceedings of the 37th conference on Winter simulation
Enhancing evolutionary algorithms with statistical selection procedures for simulation optimization
WSC '05 Proceedings of the 37th conference on Winter simulation
Simulation-based multi-objective optimization of a real-world scheduling problem
Proceedings of the 38th conference on Winter simulation
Muiltiobjective optimization using nondominated sorting in genetic algorithms
Evolutionary Computation
Simulation-based multi-objective optimization of a real-world scheduling problem
Proceedings of the 38th conference on Winter simulation
User-friendly scheduling tools for large-scale simulation experiments
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
Agile optimization for coercion
Proceedings of the 39th conference on Winter simulation: 40 years! The best is yet to come
A flexible and scalable experimentation layer
Proceedings of the 40th Conference on Winter Simulation
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Traditionally, a simulation-based optimization (SO) system is designed as a black-box in which the internal details of the optimization process is hidden from the user and only the final optimization solutions are presented. As the complexity of the SO systems and the optimization problems to be solved increases, instrumentation -- a technique for monitoring and controlling the SO processes -- is becoming more important. This paper proposes a white-box approach by advocating the use of instrumentation components in SO systems, based on a component-based architecture. This paper argues that a number of advantages, including efficiency enhancement, gaining insight from the optimization trajectories and higher controllability of the SO processes, can be brought out by an on-line instrumentation approach. This argument is supported by the illustration of an instrumentation component developed for a SO system designed for solving real-world multi-objective operation scheduling problems.