Search Results - subject:"Simulation Optimization"

Multi-objective simulation optimization using data envelopment analysis and genetic algorithm: Specific application to determining optimal resource levels in surgical services

Lin, Rung-Chuan; Sir, Mustafa Y.; Pasupathy, Kalyan S. - In: Omega 41 (2013) 5, pp. 881-892

resources. Simulation optimization refers to methods that search the design space (i.e., the set of all feasible system … multiple objectives, traditional simulation optimization methods are ineffective to uncover the efficient frontier. We propose … a framework for multi-objective simulation optimization that combines the power of genetic algorithm (GA), which can …

Persistent link: https://www.econbiz.de/10010608449

A new age-based replenishment policy for supply chain inventory optimization of highly perishable products

Duan, Qinglin; Liao, T. Warren - In: International Journal of Production Economics 145 (2013) 2, pp. 658-671

A simulation optimization framework is proposed for supply chain inventory management of highly perishable products. A …

Persistent link: https://www.econbiz.de/10011043370

Appointment system design with interruptions and physician lateness

Klassen, Kenneth J.; Yoogalingam, Reena - In: International Journal of Operations & Production Management 33 (2013) 4, pp. 394-414

study. Simulation optimization is used to simultaneously account for uncertainty and to determine (near) optimal scheduling … environmental variables and stochastic elements of the model are simultaneously accounted for by the simulation optimization … algorithm. The (very few) prior papers that have used simulation optimization have not addressed the factors studied here. …

Persistent link: https://www.econbiz.de/10014790237

Automated Response Surface Methodology for Stochastic Optimization Models with Unknown Variance

Nicolai, Robin P.; Dekker, Rommert - Tinbergen Institute - 2005

Response Surface Methodology (RSM) is a tool that was introduced in the early 50´s by Box and Wilson (1951). It is a collection of mathematical and statistical techniques useful for the approximation and optimization of stochastic models. Applications of RSM can be found in e.g. chemical,...

Persistent link: https://www.econbiz.de/10005137125

Automated Response Surface Methodology for Stochastic Optimization Models with Unknown Variance

Nicolai, R.P.; Dekker, R. - Erasmus University Rotterdam, Econometric Institute - 2005

Response Surface Methodology (RSM) is a tool that was introduced in the early 50Â´s by Box and Wilson (1951). It is a collection of mathematical and statistical techniques useful for the approximation and optimization of stochastic models. Applications of RSM can be found in e.g. chemical,...

Persistent link: https://www.econbiz.de/10004991141

Automated response surface methodology for stochastic optimization models with unknown variance

Nicolai, Robin P.; Dekker, Rommert - 2005

Response Surface Methodology (RSM) is a tool that was introduced in the early 50's by Box and Wilson (1951). It is a collection of mathematical and statistical techniques useful for the approximation and optimization of stochastic models. Applications of RSM can be found in e.g. chemical,...

Persistent link: https://www.econbiz.de/10011343271

Automated Response Surface Methodology for Stochastic Optimization Models with Unknown Variance

Nicolai, Robin P.; Dekker, Rommert - 2005

Persistent link: https://www.econbiz.de/10010325402

Automated Response Surface Methodology for Stochastic Optimization Models with Unknown Variance

Nicolai, R.P.; Dekker, Rommert - Faculteit der Economische Wetenschappen, Erasmus … - 2005

Persistent link: https://www.econbiz.de/10010837936

Automated Response Surface Methodology for Stochastic Optimization Models with Unknown Variance

Nicolai, Robin P.; Dekker, Rommert - Tinbergen Instituut - 2005

Persistent link: https://www.econbiz.de/10011255949

Multi-reservoir Operation Rules: Multi-swarm PSO-based Optimization Approach

Ostadrahimi, Leila; Mariño, Miguel; Afshar, Abbas - In: Water Resources Management 26 (2012) 2, pp. 407-427

parameterization–simulation–optimization (parameterization SO) approach. To improve the performance of the standard particle swarm … rule are estimated by employing a parameterization–simulation–optimization approach, in which a full-scale simulation model …

Persistent link: https://www.econbiz.de/10010997795