Multi-Objective Control Optimization for Greenhouse Environment Using Evolutionary Algorithms

Hu, Haigen; Xu, Lihong; Wei, Ruihua; Zhu, Bingkun

doi:10.3390/s110605792

Cited by 55 publications

(30 citation statements)

References 22 publications

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“…A successful grafting of vegetables requires high relative humidity (RH) and optimal temperature for one week following grafting to reduce transpiration of the scion until rootstock and scion vascular tissue are healed together and water transport is restored. Generally in the healing room, according to the seedlings cultivar, the adjustable temperature ranges from 15°C to 27°C with a control precision of ±0.5°C, relative humidity (RH) can be controlled within the range of 60% to 95% with control precision of ±3% and the light adjustable range is from 0 to 5000 lx [2]. According to Rivard and Louws [3] presented in Figure 1, the whole process from seeding to grafting, healing and transplanting in the field lasts five weeks.…”

Section: Introductionmentioning

confidence: 99%

An overview of the microclimate conditions inside healing chambers

Dumitrescu

Ghiaus

2019

E3S Web Conf.

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In the civil and industrial construction engineering, the comfort of occupants is ensured by achieving appropriate microclimate conditions. The human physical comfort (thermal, visual, acoustic) is achieved when the person from an enclosure is in a state of equilibrium and is able to perform tasks with maximum possible efficiency and without any kind of stress. Similarly, in the case of crops grown inside protected spaces, for plants, just as in the case of human being, specific microclimate conditions need to be ensured for their optimum development during the vegetation period. Plant development is a result of its own genetic features, but this is influenced by microclimate conditions inside of the greenhouses. Even more, in the case of healing and acclimatization rooms for grafted vegetables, the specific microclimate conditions must be strictly monitored. Technologically, it is recommended an optimum indoor temperature between 23°C and 25°C, with a maximum value that must not exceed 28°C, under conditions of relative humidity around 85% - 95%. Other two important aspects are the CO2 concentration and the level of solar radiation. The value of the CO2 concentration is an indicator of the healing process. For the grafting process, it is useful to know the time of the connection of the donor and receiver. Led by the the light levels, the photosynthetic activity of the grafted seedlings in the healing period, lead to a decreasing of CO2 concentration. This means that the two parts of the planting material are jointed, healed. So, the farmers can manipulate the environment in the healing rooms. This paper presents an overview of the scientific and technical issues that have to be achieved in order to reach suitable control and management of microclimate conditions in healing rooms for grafted vegetables.

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Section: Introductionmentioning

confidence: 99%

An overview of the microclimate conditions inside healing chambers

Dumitrescu

Ghiaus

2019

E3S Web Conf.

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“…Greenhouse climate control has led to significant improvements in the efficiency and performance of agriculture. However, greenhouse climate is a complex, nonlinear, and uncertain system, involving environmental factors like temperature, humidity, light, CO 2 concentration, and so forth [1]. Thus, optimizing greenhouse climate is a key goal for today's advanced agriculture [2,3].…”

Section: Introductionmentioning

confidence: 99%

Optimizing Greenhouse Lighting for Advanced Agriculture Based on Real Time Electricity Market Price

Mahdavian

Wattanapongsakorn

2017

Mathematical Problems in Engineering

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The world’s growing demand for food can be met by agricultural technology. Use of artificial light to supplement natural sunlight in greenhouse cultivation is one of the most common techniques to increase greenhouse production of food crops. However, artificial light requires significant electrical energy, which increases the cost of greenhouse production and can reduce profit. This paper models the increments to greenhouse productivity as well as the increases in cost from supplemental electric lighting, in a situation where the greenhouse is one of the elements of a smart grid, a system where the electric energy market is dynamic and prices vary over time. We used our models to calculate the optimum values for supplemental light and the required electrical energy for HPS lamps in the greenhouse environment, using cherry tomato cultivation as a case study crop. We considered two optimization techniques: iterative search (IS) and genetic algorithm (GA). The two approaches produced similar results, although the GA method was much faster. Both approaches verify the advantages of using optimal supplemental light in terms of increasing production and hence profit.

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“…Multiobjective evolutionary algorithms have attracted widespread attention and have been applied successfully in many areas, such as test task scheduling problem (TTSP) [1], reservoir operation [2], proportional integral and derivative (PID) controller [3], and distribution feeder reconfiguration (DFR) [4]. One key challenge in multiobjective evolutionary algorithms is the problem of resolving local optima and the speed of convergence.…”

Section: Introductionmentioning

confidence: 99%

The Effects of Using Chaotic Map on Improving the Performance of Multiobjective Evolutionary Algorithms

Wang

Fei

et al. 2014

Mathematical Problems in Engineering

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Chaotic maps play an important role in improving evolutionary algorithms (EAs) for avoiding the local optima and speeding up the convergence. However, different chaotic maps in different phases have different effects on EAs. This paper focuses on exploring the effects of chaotic maps and giving comprehensive guidance for improving multiobjective evolutionary algorithms (MOEAs) by series of experiments. NSGA-II algorithm, a representative of MOEAs using the nondominated sorting and elitist strategy, is taken as the framework to study the effect of chaotic maps. Ten chaotic maps are applied in MOEAs in three phases, that is, initial population, crossover, and mutation operator. Multiobjective problems (MOPs) adopted are ZDT series problems to show the generality. Since the scale of some sequences generated by chaotic maps is changed to fit for MOPs, the correctness of scaling transformation of chaotic sequences is proved by measuring the largest Lyapunov exponent. The convergence metricγand diversity metric Δ are chosen to evaluate the performance of new algorithms with chaos. The results of experiments demonstrate that chaotic maps can improve the performance of MOEAs, especially in solving problems with convex and piecewise Pareto front. In addition, cat map has the best performance in solving problems with local optima.

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Multi-Objective Control Optimization for Greenhouse Environment Using Evolutionary Algorithms

Cited by 55 publications

References 22 publications

An overview of the microclimate conditions inside healing chambers

An overview of the microclimate conditions inside healing chambers

Optimizing Greenhouse Lighting for Advanced Agriculture Based on Real Time Electricity Market Price

The Effects of Using Chaotic Map on Improving the Performance of Multiobjective Evolutionary Algorithms

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