Please use this identifier to cite or link to this item: http://dspace.mediu.edu.my:8181/xmlui/handle/1721.1/5134
Title: Steepest Ascent Decomposition Methods for Mathematical Programming/Economic Equilibrium Energy Planning Models
Issue Date: 9-Oct-2013
Publisher: Massachusetts Institute of Technology, Operations Research Center
Description: A number of energy planning models have been proposed for combining econometric submodels which forecast the supply and demand for energy commodities with a linear programming submodel which optimizes the processing and transportation of these commodities. We show how convex analysis can be used to decompose these planning models into their econometric and linear programming components. Steepest ascent methods are given for optimizing the decomposition, or equivalently, for computing economic equilibria for the planning models.
Supported in part by the U.S. Army Research Office (Durham) under Contract No. DAHC04-73-C-0032.
URI: http://koha.mediu.edu.my:8181/xmlui/handle/1721
Other Identifiers: http://hdl.handle.net/1721.1/5134
Appears in Collections:MIT Items

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