A Model of Automatic Block Reallocation in the Land Consolidation Projects Using Artificial Bee Colony Algorithm

Equitably reallocating of blocks among land owners has been one of the most important tasks in Land Consolidation studies. This task has to be fairly solved among landholdings for a land. This complicated problem is difficult to solve using linear methods. Therefore, a method is needed to solve this non-linear problem among land owners impartially. There are many applications employing optimization algorithms for solving the complicated and non-linear problems in literature. When we examine the literature, it is seen that Genetic Algorithm has been only used to overcome the block reallocation problem. Artificial Bee Colony (ABC) algorithm is one of the optimization algorithms that have been used to solve the non-linear and complicated problems in literature. Furthermore, this method has better performance when it is compared with the other optimization algorithms. In this study, we have aimed to fairly reallocate the landholding areas to blocks in a land by developing an algorithm using Artificial Bee Colony optimization method. When we develop the steps of the algorithm, we give priority to landholdings preferences and places of fixed installations. Data tables have been arranged by taking land consolidation data of DOT Village in Adiyaman, Turkey that into consideration. DOT Village land consolidation project includes 143 blocks and 225 landholders. Consequently, we have introduced the steps of an algorithm solving the block reallocation problem automatically using ABC for a sample land. Also, we have observed the applicability of the proposed method for automatic block reallocation problem in this study. This study is a preliminary study helping us to develop software providing to automatically solve complicated block reallocation problem in real time land consolidation process.

Keywords:

Artificial Bee Colony Algorithm, Land Consolidation, Automatic Block Reallocation Landholding, Optimization,

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