Evolutionary Hierarchical Harvest Schedule Optimization for Food Waste Prevention

Maurice Günder, Nico Piatkowski, Laura von Rueden, Rafet Sifa, Christian Bauckhage

Keywords: adaptive mutation, evolution strategy, evolutionary algorithm, Gaussian process regression, harvest schedule, hierarchical loss, optimization

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.