Enhancing Web-Spatial DSS interactivity with parallel computing: The case of bio-energy economic assessment in Greece
AbstractA web based Spatial Decision Support System (web SDSS) has been implemented in Thessaly, the most significant arable cropping region in Greece, in order to evaluate selected energy crop supply. The web SDSS uses an optimization module to support the decision process, incorporating user input from the web user interface then launching mathematical programming profit maximizing farm models. Energy to biomass raw material cost is provided in supply curve form incorporating physical land suitability for crops, farm structure and Common Agricultural Policy (CAP) scenarios. In order to generate biomass supply curves the optimization problem is parametrically solved for a number of steps within a price range determined by the user. The more advanced technique used to solve the MP model, the higher the delay of response to the user. We are examining how effectively we can reduce the web SDSS response time to the user requests using parallel solving of the corresponding optimization problem. The results are encouraging, as the total solution time drops significantly as the problem’s size is increased, improving the users’ experience.
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Bibliographic InfoPaper provided by Agricultural University of Athens, Department Of Agricultural Economics in its series Working Papers with number 2011-2.
Length: 8 pages
Date of creation: 2011
Date of revision:
Web Spatial Decision Support System; Parallel Computing; Mathematical Programming; Energy Crop Supply;
Other versions of this item:
- D. Kremmydas & A. Petsakos & S. Rozakis, 2012. "Parametric Optimization of Linear and Non-Linear Models via Parallel Computing to Enhance Web-Spatial DSS Interactivity," International Journal of Decision Support System Technology (IJDSST), IGI Global, vol. 4(1), pages 14-29, January.
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
- Q11 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Aggregate Supply and Demand Analysis; Prices
This paper has been announced in the following NEP Reports:
- NEP-AGR-2011-07-13 (Agricultural Economics)
- NEP-ALL-2011-07-13 (All new papers)
- NEP-ENE-2011-07-13 (Energy Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Michael Creel & William Goffe, 2008.
"Multi-core CPUs, Clusters, and Grid Computing: A Tutorial,"
Society for Computational Economics, vol. 32(4), pages 353-382, November.
- William L. Goffe & Michael Creel, 2005. "Multi-core CPUs, Clusters and Grid Computing: a Tutorial," Computing in Economics and Finance 2005 438, Society for Computational Economics.
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