Multi-period Two-stage Stochastic Mobile Facility Location Problem in Fresh Food Harvesting

This research presents a multi-period, two-stage stochastic mobile facility (MF) location problem (2S-SMFLP) related to fresh food harvesting. The objective is to determine the optimal locations for MFs and allocate personnel prior to the delivery of fresh food to designated facilities. This comprehensive methodology encompasses two levels: the design level, which addresses the location of MFs, staffing, and mobile routing decisions, and the operational level, which focuses on transportation and penalties for non-compliance. We calibrate decisions to minimize expected costs associated with the location and transportation scheme within the harvesting system, accounting for uncertain yields. This study considers a planning horizon characterized by fluctuating yields of fresh produce across multiple periods. As a result, the 2S-SMFLP under stochastic yield presents a complex multistage decision problem. We employ a two-stage stochastic harvesting approach with linear recourse, which is suitable given the strategic nature of the problem. The size of the stochastic set is adjusted using the sample average approximation (SAA) method. The Benders Decomposition (BD) technique is utilized to efficiently decompose and solve the two-stage stochastic model. Computational experiments are conducted based on various distributions to validate the model. We compare the deterministic harvesting model with the stochastic harvesting model for fresh food. The results of the computations demonstrate that this method holds practical value for the harvesting of fresh food.