Research and Development of Improved NSGA-II Algorithm for Optimal Path Planning for Palm Oil Drones

Tan, Wei Hang (2023) Research and Development of Improved NSGA-II Algorithm for Optimal Path Planning for Palm Oil Drones. Final Year Project (Bachelor), Tunku Abdul Rahman University of Management and Technology.

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Abstract

Palm oil is an edible vegetable oil that can be used in a range of products such as food (chocolate, cooking oil), industrial applications (soap), and bioenergy. The palm oil industry contributes around 3.6% of Malaysia's overall GDP, making it the country's second-largest producer and exporter of palm oil worldwide. In Malaysia, there are around 500000 plantation workers in palm oil industries. However, this led to certain problems for the palm oil sector due to human limits. As a result, drones will be utilized to support the palm oil businesses, but their battery life is limited, so they may not be able to fly the full area of the palm oil farm. Therefore, a Non-Dominated Sorting Algorithm II with an improved genetic algorithm is developed to perform the determination of the optimal path with minimum turning angle and elevation of the drone. Enhancement of the algorithm is done by improving the selection, crossover, and mutation operations of the genetic algorithm which improves the convergence rate and diversity of the algorithm, allowing it to locate the optimum solution while also preventing a fall into the local optimal. The proposed algorithm is applicable to solve the problems described in this research. In the majority of files, it is able to discover the solution with a voltage that is lower than the reference voltage of the firm. Last but not least, the proposed algorithm can solve each file in under 10 minutes, which satisfies this research's requirements.