Robust Optimization in Integrated Harvesting and Processing Scheduling of Strawberry Under Demand Uncertainty

Abstract

Harvesting scheduling is decision-making techniques to determine the location and the appropriate harvest time, so as to meet the demand and to maximize the profit. An effective scheduling model started from harvesting, processing, and storage of strawberry has been formulated using Mixed Integer Linear Programming. In this paper, Robust Optimization is formulated for the strawberry harvesting scheduling problem without considering product decay during storage, to overcome the uncertainty of consumer demand. Through the formulation of Robust Counterpart, we assume the uncertainty of consumer demand is in the box uncertainty set and ellipsoidal uncertainty set, to obtain Robust Counterpart that computationally tractable. Furthermore numerical simulations carried out by Branch and Bound Method using Maple application software, in order to obtain optimal robust solution.