https://www.imosver.com/en/libros/introduction-to-stochastic-programming-A000030888A000030888Introduction to stochastic programming11.4Optimization is one of the most reliable mathematical tool for decisión making. Since the 50?s, it is well known that traditional deterministic optimaztion is not appropriate for capturing the uncertahttps://static.serlogal.com/imagenes_small/9788498/978849849454.jpgLibrosSin stock temporalmenteDYKINSON000https://static.serlogal.com/imagenes_small/9788498/978849849454.jpg1250.62009/01/019788498494549Alonso-Ayuso, AntonioLibrosaño_2009idioma_EnglishIformato_Tapa blanda o Bolsilloautor_Alonso-Ayuso, Antoniosaga_Colección Ciencias Experimentales y Tecnología
Artículo
Introduction to stochasti
Alonso-Ayuso Antonio
DYKINSON
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Optimization is one of the most reliable mathematical tool for decisión making. Since the 50?s, it is well known that traditional deterministic optimaztion is not appropriate for capturing the uncertain behavior present in most real world applications. Moreover, it was not until the 80?s when stochastic programming was broad applied in real-world applications. Moreover, it was not until the 80?s when stochastic programming was broad applied in real-world applications. Uncertainty is the key ingredient in many decision problemas. Financial planing, airline scheduling and unit commitmen in power systems are just few examples of aereas in wich ignoring uncertainty may lead to inferior or simply wrong decisions. There are several ways in wich uncertainty can be formalized and over the past thirty years varioud approaches to optimization under uncertainty have been developed. The fiel of Stochastic programming (SP) appears as a response to the need of incorporating uncertainty in mathematical models. Basically, it deals with mathematical programs in which some parameters are random variables.