Hybrid Biogeography-Based Optimization for Solving Tomato Planting Planning

Abstract

How to solve the unbalanced supply of raw tomato is a difficult problem which puzzles ketchup factory for a long period of time. Biogeography-based optimization (BBO) is proposed to solve tomato planting planning problem. Nonlinear mathematical model of tomato planting planning is constructed. Some strategies, such as cosine migration model, disturbing migration operator, mutation operator based on Gaussian distribution, and the reasonable combination of mutation operator of differential evolution algorithm (DE) and chaos technology, were used to improve the exploitation and exploration performance of BBO. The problem of planting planning is transformed into the combination optimization problem. We take a Ketchup factory of Xinjiang in China as an example. The simulation results show that the proposed algorithm can meet the balance between raw tomato material production and Ketchup factory capacity. And the proposed algorithm compares with other intelligent optimization algorithms. It verifies rationality of the presented mathematical model and good astringency and feasibility of the proposed algorithm. Thus, optimal planting planning for tomato planting can be achieved.