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How to use or fill out the A Cutting-plane Method For Contiguity-constrained Spatial Aggregation online
This guide provides step-by-step instructions for filling out the A Cutting-plane Method For Contiguity-constrained Spatial Aggregation form online. By following these clear instructions, you will be able to complete the form accurately and efficiently.
Follow the steps to successfully fill out the form.
- Click the ‘Get Form’ button to obtain the form and open it for editing.
- Review the introductory section of the form. Familiarize yourself with the purpose of the form, which is to apply a cutting-plane method for spatial aggregation while ensuring contiguity constraints.
- Fill out the required fields on the form. You will typically encounter sections that ask for information such as the parameters for the aggregation problem, such as area units, population limits, and any specific attributes or constraints that must be considered.
- In the section relating to contiguity constraints, specify the necessary conditions that the aggregated areas must fulfill. Make sure the entries align with the boundary conditions defined in the methodology.
- Review any optional fields provided in the form that might enhance your application, such as additional comments or methodological notes that support your aggregation process.
- Once all necessary fields are filled out, review your entries for accuracy. Ensure that all details are correctly entered to avoid any discrepancies in the processing of your submission.
- After verifying your information, proceed to save changes to the form. You can also download, print, or share the completed form as required for your records.
Complete your A Cutting-plane Method For Contiguity-constrained Spatial Aggregation today to ensure efficient spatial planning and data visualization.
The idea of Kelley's cutting plane algorithm is to approximate the feasible region with a polytope, solve the resulting linear program (LP) and, if the LP solution is not feasible, separate it using gradient cuts to obtain a new polytope which is a better approximation of the feasible region and repeat, see Algorithm 1 ...
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