Innovative models for supporting operational planning. (1st January 2014)

• Record Type: Journal Article
• Authors: Massei, Marina; Poggi, Simonluca; Tremori, Alberto; Ferrando, Angelo
• Is Part Of: International journal of simulation and process modelling. Volume 9:Number 3(2014)
• Page Start: 181
• Page End: 194
• Publication Date: 2014-01-01
• Subjects: simulation for stabilisation and reconstruction -- simulation for S&R -- civil military cooperation -- CIMIC -- psychological operations -- PSYOPs -- human behaviour modifiers -- HBM; Management -- Computer simulation -- Periodicals; Mathematical models -- Periodicals; Operations research -- Periodicals; Simulation methods -- Periodicals; 003.05
• Languages: English
• ISSNs: 1740-2123

Abstract

Innovative simulation models are proposed for supporting operational planning related to civil military cooperation (CIMIC) and psychological operations (PSYOPs) within complex scenarios. The paper describes these models as well as the experimentation in situations involving crisis and conflicts (i.e., Afghanistan); these models are based on the intelligent agent computer generated forces (IA-CGF) developed by simulation team and they have been extensively used in CIMIC and planning research in complex operational realistic network (CAPRICORN) project, an initiative led by University of Genoa for European Defense Agency (EDA). The proposed models take care both of logistics and operational issues as well as of the effects on the people and interest groups; indeed the paper proposes the simulator developed to demonstrate these capabilities that include the communications among the stakeholders, the population models as well as the effects of human factors including social and cultural aspects. The paper includes experimental results based on this simulator devoted to validate and test the models in strong cooperation with final users and subject matter experts (SME); the proposed experimentation is based on design of experiment techniques including mean square pure error (MSpE) and sensitivity analysis.