Mathematical Programming Models for Fresh Fruit Supply Chain Optimization: A Review of the Literature and Emerging Trends

The fresh fruit agricultural and distribution sector is faced with risks and uncertainties from climate change, water scarcity, land-use increase for industrial and urban development, consumer behavior, and price volatility. The planning framework for production and distribution is highly complex as a result. Mathematical models have been developed over the decades to deal with this complexity. With improvements in both processor speed and memory, these models are becoming increasingly sophisticated. This review focuses on the recent progress in mathematically based decision making to account for uncertainties in the fresh fruit supply chain. The models in the literature are mostly based on linear and mixed integer programming and involve variants such as stochastic programming and robust optimization. The functional areas of application include planting, harvest optimization, logistics and distribution. The perishability of the fresh fruit supply chain is an important issue as is the cycle time of cultivation and harvest.

Automated summary

The fresh fruit agricultural and distribution sector faces risks and uncertainties from climate change, water scarcity, land-use increase, consumer behavior, and price volatility. Mathematical models, mainly based on linear and mixed integer programming, have been developed to deal with this complexity, with advancements in processor speed and memory leading to increasingly sophisticated models. These models are applied in various areas such as planting, harvest optimization, logistics, and distribution, addressing the perishability of the fresh fruit supply chain and cycle time of cultivation and harvest as important issues.