Stochastic programming and scenario generation within a simulation framework: An information systems perspective

作     者：Di Domenica, Nico Mitra, Gautam Valente, Patrick Birbilis, George 

作者机构：Brunel Univ Sch Informat Syst CARISMA Uxbridge UB8 3PH Middx England 

出 版 物：《DECISION SUPPORT SYSTEMS》 (决策支持系统)

年 卷 期：2007年第42卷第4期

页      面：2197-2218页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：scenario generation stochastic programming DSS OLAP business analytics simulation 

摘      要：Stochastic programming brings together models of optimum resource allocation and models of randomness to create a robust decision-making framework. The models of randomness with their finite, discrete realisations are called scenario generators. In this paper, we investigate the role of such a tool within the context of a combined information and decision support system. We explain how two well-developed modelling paradigms, decision models and simulation models can be combined to create business analytics which is based on ex-ante decision and ex-post evaluation. We also examine how these models can be integrated with data marts of analytic organisational data and decision data. Recent developments in on-line analytical processing (OLAP) tools and multidimensional data viewing are taken into consideration. We finally introduce illustrative examples of optimisation, simulation models and results analysis to explain our multifaceted view of modelling. In this paper, our main objective is to explain to the information systems (IS) community how advanced models and their software realisations can be integrated with advanced IS and DSS tools. (c) 2006 Elsevier B.V. All rights reserved.