• Refine Query
  • Source
  • Publication year
  • to
  • Language
  • 1
  • Tagged with
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • 1
  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Machinery selection and scheduling model for Virginia

Xiong, Huanbao 10 July 2009 (has links)
A field machinery selection model originally developed by Dr. John C. Siemens for Illinois has been fully studied and adapted to Virginia agriculture. The modified version of this model is able to assist farm managers in selecting optimum machinery sets for multiple cropping production systems. The program was written in the C programming language to run on an IBM compatible personal computer. The program input information consists of a list of desired field operations with start date, acres, and hours per day for each operation. Other input includes crop yields, penalty dates for planting and harvesting, availability and cost of labor, and certain economic data such as crop and fuel prices and interest rates. Stored data files contain machine list prices and productivity values, workday probabilities, and equation constants for computing machine costs. For different machinery sets or a specified set of machinery, the program schedules the field operations and computes the total machinery related costs including costs for the machines, labor, and timeliness. Using an optimization process, the lowest cost machinery set is determined and the eight lowest cost sets found during the process are presented. For any of the eight lowest cost sets, or for a specific set of machinery, the output includes a list of the machinery with prices and annual use, the work schedule, the cost for each operation, and total machinery related costs. / Master of Science

Page generated in 0.058 seconds