The OptQuest Engine provides a tool to facilitate the development of applications that require the optimization of complex systems that may or may not utilize simulation. It provides user-friendly software to customers who may have limited knowledge of how optimization works yet who need access to the sophisticated optimization techniques.
Keywords for this software
References in zbMATH (referenced in 12 articles )
Showing results 1 to 12 of 12.
- Lucidi, Stefano; Maurici, Massimo; Paulon, Luca; Rinaldi, Francesco; Roma, Massimo: A derivative-free approach for a simulation-based optimization problem in healthcare (2016)
- Ajdari, Ali; Mahlooji, Hashem: An adaptive exploration-exploitation algorithm for constructing metamodels in random simulation using a novel sequential experimental design (2014)
- Nikolaidis, Yiannis (ed.): Quality management in reverse logistics. A broad look on quality issues and their interaction with closed-loop supply chains (2013)
- Charnes, John: Financial modeling with Crystal Ball and Excel (2012)
- Bekker, James; Aldrich, Chris: The cross-entropy method in multi-objective optimisation: an assessment (2011)
- Lejeune, Miguel A.; Margot, François: Optimization for simulation: LAD accelerator (2011)
- Kleijnen, Jack P. C.: Design and analysis of computational experiments: overview (2010)
- Kleijnen, Jack P. C.; van Beers, Wim; van Nieuwenhuyse, Inneke: Constrained optimization in expensive simulation: novel approach (2010)
- Xu, Jie; Nelson, Barry L.; Hong, Jeff L.: Industrial strength COMPASS: a comprehensive algorithm and software for optimization via simulation (2010)
- Bettonvil, Bert; Del Castillo, Enrique; Kleijnen, Jack P. C.: Statistical testing of optimality conditions in multiresponse simulation-based optimization (2009)
- Kleijnen, Jack P. C.; Wan, Jie: Optimization of simulated systems: OptQuest and alternatives (2007) ioport
- Thiriez, Hervé: Improved OR education through the use of spreadsheet models (2001)