Author(s)

Caicong Wu^1,2, Lin Zhou¹, Peng Qiao¹, Jie Wang¹

¹College of Information and Electrical Engineering, China Agricultural University, Beijing, China.
²Department of Soil & Crop Sciences, Texas A&M University, College Station, USA.

Uncertainty is an important characteristic of scheduling model for scale farm machinery operation organizing. Practice shows that scheduling model without considering uncertainties is nearly useless. Uncertain influence factors arisen from natural environment, society and economy, market and supply, and customer and behavior, exist widely, emerge frequently, and affect production deeply. Uncertainties interfere with the allocation of productive factors on temporal and spatial dimensions for farm machinery operation scheduling and management. Questionnaire for farm machinery organizations was designed and finished in 2014. Both occurrence frequency and influence degree for each factor were quantified. Four influence factors including operation location change, weather mutation, parts supply delay, and operation skill defects appear in both list of high occurrence and deep influence. Then results of questionnaire and results of specific investigation were used to study temporal and spatial scheduling model and system for farm machinery management. Three case studies are introduced. The first case is about the uncertainty and countermeasure of forage harvesters scheduling and monitoring for a professional forage plantation company. The second case is about the uncertainty and counter measure of cotton-picker scheduling and monitoring for a professional cotton picking company. And the third case is about the uncertainty and countermeasure of social service management for a professional cooperative. The cases show that the research has strong pertinence to deal with uncertainties and can improve management efficiency of farm machinery operation.

Uncertainty, Influence Factor, Farm Machinery, Schedule, Model, GNSS

Wu, C. , Zhou, L. , Qiao, P. and Wang, J. (2016) Addressing Uncertainty in Temporal and Spatial Scheduling for Farm Machinery Operation. Positioning, 7, 32-40. doi: 10.4236/pos.2016.71003.