Harvest Optimization of Citrus Crop Using Genetic Algorithms

Abstract

The harvest optimization problem (HOP) of the citrus crop is concerned with finding the picking schedule of the orange plots (or “blocks”) that maximizes the total net revenue. In its most simplified form the HOP is an integer-programming (IP) problem where the decision is to determine which block to pick at which week. Since the number of blocks is several hundreds and the picking season extends over 6 months, the resulting IP problem is very large which makes it hard to solve analytically. Consequently, we pursue a heuristic approach to solve the HOP involving Genetic Algorithms (GA). The GA approach is demonstrated by means of a prototype problem that is somewhat simplified, yet captures many of the components and characteristics of the real full-scale HOP. To study the sensitivity and stability of the approach, the GA model was solved on a variety of demand and supply scenarios, and was compared with a Linear-programming (LP) based solution.