Evolutionary Hierarchical Harvest Schedule Optimization for Food Waste Prevention

TL;DR

This paper presents an evolutionary algorithm-based method to optimize harvest schedules for intercropping systems, aiming to reduce food waste, lower environmental impact, and improve logistical efficiency.

Contribution

It introduces a hierarchical loss function and adaptive mutation rate to enhance convergence and solution quality in harvest schedule optimization.

Findings

Faster convergence compared to conventional methods

Improved harvest schedule quality

Effective multi-objective to pseudo-single-objective transfer

Abstract

In order to avoid disadvantages of monocropping for soil and environment, it is advisable to practice intercropping of various plant species whenever possible. However, intercropping is challenging as it requires a balanced planting schedule due to individual cultivation time frames. Maintaining a continuous harvest reduces logistical costs and related greenhouse gas emissions, and contributes to food waste prevention. In this work, we address these issues and propose an optimization method for a full harvest season of large crop ensembles that complies with given constraints. By using an approach based on an evolutionary algorithm combined with a novel hierarchical loss function and adaptive mutation rate, we transfer the multi-objective into a pseudo-single-objective optimization problem and obtain faster convergence and better solutions than for conventional approaches.