Agricultural land partitioning model based on irrigation efficiency using a multi‐objective artificial bee colony algorithm

Abstract

In the process of agricultural land consolidation, the land parcels are optimally redesigned and rearranged in such a way that the dimensions of the resulting parcels are proportional to agricultural criteria such as irrigation discharge, soil texture, and cropping pattern. Besides these criteria, spatial factors like slope, road accessibility, volume of earthwork, and geometrical factors such as size and shape of parcels are also included in the design process of agricultural land partitioning. In this study, a land partitioning model was proposed using a multi‐objective artificial bee colony algorithm (MOABC‐LP) taking into consideration the mentioned factors. Initially, a feasible dimension range of parcels in a block was calculated based on irrigation efficiency. Two partitioning layouts were defined according to the topography and geometry of blocks. The proposed method was applied to a real study area and the results suggest that the land partitioning plan obtained by the MOABC‐LP model, in comparison with a designer's plan, not only makes the shape and size of parcels more compatible with the topographical and agricultural conditions of each block, but also reduces their cut‐and‐fill ratio.

Application of Bio and Nature-Inspired Algorithms in Agricultural Engineering

“…Recent studies have also demonstrated the algorithm could augment ant colony's application in land use optimization and prediction of crop prices [134,171]. The reliability of the forecast data provided by the artificial bee colony algorithm was corroborated by forecasting models such as Support Vector Regression (SVR), ARIMA, and LSTM (see Table 7) [134].…”

“…The model employed by the natural bees enables the onlookers and workers to evaluate the suitability of the food source and the optimization of the nectar selection process [134,[170][171][172]. The ant bee colony optimization algorithm has been proven useful in a wide array of agricultural applications such as optimized data aggregation for IoT devices [172], numerical optimization, evapotranspiration monitoring [65], and zoning of protected ecological areas [143,170].…”

“…Even though there were sufficient grounds for the deployment of swarm intelligence-based algorithms in agriculture, there were limitations that hindered widespread adoption [134,139,[170][171][172]. First, the ant colony and artificial bee investigation indicated that swarm intelligence-based algorithms involve time-intensive processes, which are impacted by the iteration patterns, frequency of iterations, and population sizes.…”

Making Cities Smarter—Optimization Problems for the IoT Enabled Smart City Development: A Mapping of Applications, Objectives, Constraints

“…While combinatorial optimization algorithms have found wide ranging applications in all aspects of a city's operations for e.g., in planning [140,141] and scheduling [142], it is expected that as more aspects of a city are instrumented and data gathering takes place, applications of optimization algorithms which work on real-time measurements will be further developed. With newly instrumented systems, one could also leverage machine and deep learning algorithms for predicting a variable of interest and then utilize optimization algorithms for a given application.…”

Reallocation model in land consolidation using multi‐objective particle swarm optimization dealing with landowners' rights

“…Different models of agricultural land exploitation in Iran, such as agricultural joint‐stock companies, production cooperatives, and agro‐industries, have led to the implementation of LC in various ways in Iran. In the common process of designing LC projects in Iran, after designing the roads and the irrigation and drainage network, an optimal partitioning plan for agricultural lands is prepared considering technical criteria and allocated to the stakeholders based on the share of each owner of these parcels (Bijandi, Karimi, Farhadi Bansouleh, & van der Knaap, 2021). LC has several stages with a large number of stakeholders involved (Basista, 2020), and land reallocation is the core of the LC process and a means of regulating property rights (Ertunç, Çay, & Hakli, 2018).…”