Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Real-life simulation optimization applications often deal with large-scale simulation models that are time-consuming to execute. Parallel computing environments, such as high performance computing clusters and cloud computing services, provide the computing por needed to scale to such applications. ,  show how the Empirical Stochastic Branch and Bound algorithm, an effective globally convergent random search algorithm for discrete optimization via simulation, can be adapted to a high-performance computing environment to effectively utilize the por of parallelism.  propose a master-worker structure driven by MITRE's Goal-Directed Grid-Enabled Simulation Experimentation Environment. Numerical experiments with the popular Ackley benchmark test function and a real-world simulation called  runway Simulator demonstrate the number of cores needed to achieve a good scaled efficiency of parallel empirical stochastic branch and bound for increasing levels of simulation run times.
['Scott L. Rosen', 'Peter Salemi', 'B Wickham', 'Ashley Williams', 'Christine Harvey', 'Erin Catlett', 'Sajjad Taghiyeh', 'Jie Xu']
I am writing a research paper on a idea Parallel empirical stochastic branch and bound for large-scale discrete optimization via simulation
[{"from": "human", "value": "I am writing a research paper on a idea Parallel empirical stochastic branch and bound for large-scale discrete optimization via simulation"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Real-life simulation optimization applications often deal with large-scale simulation models that are time-consuming to execute. Parallel computing environments, such as high performance computing clusters and cloud computing services, provide the computing por needed to scale to such applications. ,  show how the Empirical Stochastic Branch and Bound algorithm, an effective globally convergent random search algorithm for discrete optimization via simulation, can be adapted to a high-performance computing environment to effectively utilize the por of parallelism.  propose a master-worker structure driven by MITRE's Goal-Directed Grid-Enabled Simulation Experimentation Environment. Numerical experiments with the popular Ackley benchmark test function and a real-world simulation called  runway Simulator demonstrate the number of cores needed to achieve a good scaled efficiency of parallel empirical stochastic branch and bound for increasing levels of simulation run times."}]