| The selection of the least-cost machinery complement is a complex problem. This is because a machinery complement decision is greatly influenced by several factors: the available number of field workdays which vary from year to year, the availability of labor, wage rate, crop mix, and the desire for leisure time.; The main objective of this study was to develop a mathematical programming model for selecting optimal machinery complements for irrigated farms in the Columbia Basin project area of central Washington. A mixed integer programming model was developed to determine the least cost, number, and sizes of machines and equipment for a specified farm size and crop mix.; Input data required for the program were: field operations to be performed, acreage of each crop, days available for field work, hours available for work per day, machinery field capacity, and purchase prices of machines and equipment. Cost of labor and labor availability per field workday also were used as input data.; Three hypothetical farms were identified for this analysis. Farm size, crop mix, and machinery available for selection were assumed different for each farm size, all else was the same. The three hypothetical farms were the 390-acre, the 650-acre, and the 910-acre farm.; The least-cost machinery complements determined included one tractor for the 390-acre farm and two tractors each for the 650-acre and 910-acre farms. The sensitivity of the machinery complement for the 650-acre farm was tested with respect to reduced timeliness, change in wage rates, and custom-hire availability. In all three hypothetical farms, custom-hired operations were selected for some harvest activities. |
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