Optimal production planning and machinery scheduling for semi-arid farms

Daniel A. Zuniga Vazquez, Neng Fan, Trent Teegerstrom, Clark Seavert, Hailey M. Summers, Evan Sproul, Jason C. Quinn

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Scarce water resources have made production planning a key management decision in the agriculture sector, especially in arid and semi-arid regions. To address this issue, farmers can gradually adopt low-water-use crops, such as guar and guayule, which have great potential for the agricultural economy of the Southwestern U.S. The farmers’ profits can be further increased by reducing machinery transportation costs through optimized scheduling. For such purpose, this paper introduces a farm production planning and machinery scheduling optimization model for perennial and non-perennial crops that maximizes the farmers’ net present value. The optimization model allows for multi-crop production planning, multi-machinery scheduling, and crop rotation. To address the water scarcity problem in arid and semi-arid regions, perennial and non-perennial low-water-use crops can be considered in the crop rotation. Based on the Geographic Information System, the optimal scheduling routes are determined and the irrigation water requirements are analyzed. The resulting model yields a complex large-scale integer linear optimization problem. The model is assessed on two case studies, one for the guar crop (non-perennial) considering parcels located at the Cochran and Hockley counties in Texas and another case study for the guayule crop (perennial) considering parcels located in Pinal County in Arizona.

Original languageEnglish (US)
Article number106288
JournalComputers and Electronics in Agriculture
Volume187
DOIs
StatePublished - Aug 2021

Keywords

  • Crop rotation
  • Low-water-use crops
  • Machinery scheduling
  • Production planning

ASJC Scopus subject areas

  • Forestry
  • Agronomy and Crop Science
  • Computer Science Applications
  • Horticulture

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