{'fraction_non_alphanumeric': 0.015803336259877086, 'fraction_numerical': 0.0, 'mean_word_length': 6.037037037037037, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
A multiobjective approach to hierarchical control of greenhouse crop production

The problem of determining the trajectories to control the greenhouses crop growth has been traditionally solved by using constrained optimization or applying artificial intelligence techniques. The economic profits have been used as the main criteria in most of the research on optimization to obtain adequate climatic control references for the crop growth. This paper addresses the problem of the greenhouse crop growth control from a multiobjective optimization approach, proposing and solving a problem where several objectives, that are in conflict between them, are used to find reference trajectories for diurnal and nocturnal temperatures (climate-related set points) and electrical conductivity (fertirrigation-related set points). The objectives are to maximize profits, fruit quality and water use efficiency, these being currently fostered by international regulations. The multiobjective optimization approach is embedded within a hierarchical control scheme, where climate, irrigation and crop growth models are used for optimization purposes.