Harvest optimization for sustainable agriculture:The case of tea harvest scheduling
作者机构:Department of Industrial EngineeringFaculty of Architecture and EngineeringKırıkkale UniversityKırıkkaleTurkey
出 版 物:《Artificial Intelligence in Agriculture》 (农业人工智能(英文))
年 卷 期:2023年第10卷第4期
页 面:35-45页
核心收录:
学科分类:082804[工学-农业电气化与自动化] 08[工学] 0828[工学-农业工程]
主 题:Goal programming Harvest optimization Harvest scheduling Sustainable agriculture Tea
摘 要:To ensure sustainability in agriculture,many optimization problems need to be *** important one of them is harvest scheduling *** this study,the harvest scheduling problem for the tea is *** tea harvest problem includes the creating a harvest schedule by considering the farmers quotas under the purchase location and factory *** harvesting is carried out in cooperation with the *** man-agement is interested in using its ***,the factory capacity,purchase location capacities and number of expeditions should be considered during the harvesting *** the farmer s side is examined,it is seen that the real professions of farmers are *** harvest days,farmers often cannot attend to their primary *** the harvest day preferences of farmers in creating the harvest schedule are of great importance for sustainability in *** different mathematical models are proposed to solve this *** first model minimizes the number of weekly expeditions of factory vehicles within the factor and purchase location capacity *** second model minimizes the number of expeditions and aims to comply with the preferences of the farmers as much as possible.A sample application was performed in a region with 12 purchase locations,988 farmers,and 3392 decares of tea *** results show that the compli-ance rate of farmers to harvesting preferences could be increased from 52%to 97%,and this situation did not affect the number of expeditions of the *** result shows that considering the farmers preferences on the harvest day will have no negative impact on the *** the contrary,it was concluded that this situation increases sustainability and encouragement in ***,the results show that models are effective for solving the problem.