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Effective environmental decision-making is often challenging and complex, where final solutions frequently possess inherently subjective political and socio-economic components. Consequently, complex sustainability applications in the “real world” frequently employ computational decision-making approaches to construct solutions to problems containing numerous quantitative dimensions and considerable sources of uncertainty. This volume includes a number of such applied computational analytics papers that either create new decision-making methods or provide innovative implementations of existing methods for addressing a wide spectrum of sustainability applications, broadly defined. The disparate contributions all emphasize novel approaches of computational analytics as applied to environmental decision-making and sustainability analysis – be this on the side of optimization, simulation, modelling, computational solution procedures, visual analytics, and/or information technologies.

Research & information: general --- Mathematics & science --- streamflow forecasting --- C-vine copula --- quantile regression --- joint dependencies --- water resource management --- ecological relationship --- factorial analysis --- input-output analysis --- optimal path --- reduction --- urban solid waste system --- desalination --- reverse osmosis --- modelling --- simulation --- parameter estimation --- seawater --- boron --- watershed management --- nonpoint source pollution --- point source pollution --- water quality --- pollutant loadings --- South Texas --- eco-efficiency --- DEA --- CO2 emissions --- forecasting --- ecological indicators --- biomass gasification --- machine learning --- computer modeling --- computer simulation --- regression --- model reduction --- LASSO --- classification --- feature selection --- financial market --- investing --- sustainability --- renewable energy support --- energy modeling --- energy system design --- generation profile --- environmental footprint --- renewable energy --- electricity production --- unlisted companies --- Germany --- feed-in tariff --- biofuel policy --- investment profitability analysis --- the pay-off method --- simulation decomposition --- sourcing --- operational flexibility --- business aviation --- turboprop --- electric motor --- specific power --- Monte Carlo simulation --- Iowa food-energy-water nexus --- nitrogen export --- system modeling --- weather modeling --- optimal allocation --- interval --- fuzzy --- dynamic programming --- water resources --- n/a

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• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Effective environmental decision-making is often challenging and complex, where final solutions frequently possess inherently subjective political and socio-economic components. Consequently, complex sustainability applications in the “real world” frequently employ computational decision-making approaches to construct solutions to problems containing numerous quantitative dimensions and considerable sources of uncertainty. This volume includes a number of such applied computational analytics papers that either create new decision-making methods or provide innovative implementations of existing methods for addressing a wide spectrum of sustainability applications, broadly defined. The disparate contributions all emphasize novel approaches of computational analytics as applied to environmental decision-making and sustainability analysis – be this on the side of optimization, simulation, modelling, computational solution procedures, visual analytics, and/or information technologies.

streamflow forecasting --- C-vine copula --- quantile regression --- joint dependencies --- water resource management --- ecological relationship --- factorial analysis --- input-output analysis --- optimal path --- reduction --- urban solid waste system --- desalination --- reverse osmosis --- modelling --- simulation --- parameter estimation --- seawater --- boron --- watershed management --- nonpoint source pollution --- point source pollution --- water quality --- pollutant loadings --- South Texas --- eco-efficiency --- DEA --- CO2 emissions --- forecasting --- ecological indicators --- biomass gasification --- machine learning --- computer modeling --- computer simulation --- regression --- model reduction --- LASSO --- classification --- feature selection --- financial market --- investing --- sustainability --- renewable energy support --- energy modeling --- energy system design --- generation profile --- environmental footprint --- renewable energy --- electricity production --- unlisted companies --- Germany --- feed-in tariff --- biofuel policy --- investment profitability analysis --- the pay-off method --- simulation decomposition --- sourcing --- operational flexibility --- business aviation --- turboprop --- electric motor --- specific power --- Monte Carlo simulation --- Iowa food-energy-water nexus --- nitrogen export --- system modeling --- weather modeling --- optimal allocation --- interval --- fuzzy --- dynamic programming --- water resources --- n/a

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Effective environmental decision-making is often challenging and complex, where final solutions frequently possess inherently subjective political and socio-economic components. Consequently, complex sustainability applications in the “real world” frequently employ computational decision-making approaches to construct solutions to problems containing numerous quantitative dimensions and considerable sources of uncertainty. This volume includes a number of such applied computational analytics papers that either create new decision-making methods or provide innovative implementations of existing methods for addressing a wide spectrum of sustainability applications, broadly defined. The disparate contributions all emphasize novel approaches of computational analytics as applied to environmental decision-making and sustainability analysis – be this on the side of optimization, simulation, modelling, computational solution procedures, visual analytics, and/or information technologies.

Research & information: general --- Mathematics & science --- streamflow forecasting --- C-vine copula --- quantile regression --- joint dependencies --- water resource management --- ecological relationship --- factorial analysis --- input-output analysis --- optimal path --- reduction --- urban solid waste system --- desalination --- reverse osmosis --- modelling --- simulation --- parameter estimation --- seawater --- boron --- watershed management --- nonpoint source pollution --- point source pollution --- water quality --- pollutant loadings --- South Texas --- eco-efficiency --- DEA --- CO2 emissions --- forecasting --- ecological indicators --- biomass gasification --- machine learning --- computer modeling --- computer simulation --- regression --- model reduction --- LASSO --- classification --- feature selection --- financial market --- investing --- sustainability --- renewable energy support --- energy modeling --- energy system design --- generation profile --- environmental footprint --- renewable energy --- electricity production --- unlisted companies --- Germany --- feed-in tariff --- biofuel policy --- investment profitability analysis --- the pay-off method --- simulation decomposition --- sourcing --- operational flexibility --- business aviation --- turboprop --- electric motor --- specific power --- Monte Carlo simulation --- Iowa food-energy-water nexus --- nitrogen export --- system modeling --- weather modeling --- optimal allocation --- interval --- fuzzy --- dynamic programming --- water resources

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This research topic aims at enterprise-wide modeling and optimization (EWMO) through the development and application of integrated modeling, simulation and optimization methodologies, and computer-aided tools for reliable and sustainable improvement opportunities within the entire manufacturing network (raw materials, production plants, distribution, retailers, and customers) and its components. This integrated approach incorporates information from the local primary control and supervisory modules into the scheduling/planning formulation. That makes it possible to dynamically react to incidents that occur in the network components at the appropriate decision-making level, requiring fewer resources, emitting less waste, and allowing for better responsiveness in changing market requirements and operational variations, reducing cost, waste, energy consumption and environmental impact, and increasing the benefits. More recently, the exploitation of new technology integration, such as through semantic models in formal knowledge models, allows for the capture and utilization of domain knowledge, human knowledge, and expert knowledge toward comprehensive intelligent management. Otherwise, the development of advanced technologies and tools, such as cyber-physical systems, the Internet of Things, the Industrial Internet of Things, Artificial Intelligence, Big Data, Cloud Computing, Blockchain, etc., have captured the attention of manufacturing enterprises toward intelligent manufacturing systems.

manufacturing process --- additive manufacturing --- IoT --- computer systems and networks --- 3D printing --- digital twin --- Industry 4.0 --- pharmaceutical manufacturing --- biopharmaceutical manufacturing --- process modeling --- mixed-integer linear programming --- bin-packing problem --- material requirements planning --- agri-supply chain management --- variable production rate --- optimal resources --- imperfect production --- eco-efficient production --- closed-loop scheduling --- scheduling stability --- optimal control and scheduling --- fouling --- heat exchanger networks --- continuous manufacturing --- bioprocessing --- process systems engineering --- single-use technology --- AGV—Automated Guided Vehicles --- DES—Discrete Event Simulation --- FMS—Flexible Manufacturing Systems --- OEE—Overall Equipment Efficiency --- WCLcWorld Class Logistic --- abrasive water jet --- cutting --- surface quality --- quality prediction --- 3D simulation modeling and analysis --- model implementation --- bottleneck analysis --- production costs --- resource conservation --- smart manufacturing --- edge computing --- machine learning --- blockchain --- Industrial Internet of Things --- inventory management --- supply chain --- multi-echelon --- stochastic programming --- reinforcement learning --- digitalisation --- model-based --- computational engineering --- process simulation --- LNG terminal --- operational optimization --- BOG compressor --- MINLP --- enterprise process architecture --- new technologies integration --- process intelligence --- real-time monitoring --- fault detection --- predictive process adjustment --- vacuum gripper --- sensor data --- Tri-X Intelligence --- cyber-physical systems --- human-cyber systems --- intelligent systems --- intelligent manufacturing --- multi-parametric programming --- explicit MPC --- enterprise-wide optimisation --- set-point tracking --- algebraic geometry --- continuous pharmaceutical manufacturing --- model predictive control --- state estimation --- quality-by-control (QbC) --- glidant effects --- plant-model mismatch --- regional logistics --- low-carbon economy --- cloud model --- comprehensive evaluation --- Beijing-Tianjin-Hebei region --- pharmaceutical manufacture --- uncertainty --- operational flexibility --- operational envelopes --- modeling --- n/a --- AGV-Automated Guided Vehicles --- DES-Discrete Event Simulation --- FMS-Flexible Manufacturing Systems --- OEE-Overall Equipment Efficiency