The Red Palm Weevil (RPW) has spread over palm trees in many countries, causing economic harms estimated at multi-billion dollars annually. Palm trees are of very important economic, environmental, cultural and heritage value to Saudi Arabia, gulf countries and worldwide. There is a persistent need to fight this fatal insect scourge by halting its spread. A team of multiple Unmanned Aerial Vehicles (UAVs) equipped with suitable equipment has the potential to help by cooperating to perform an RPW detect-and-treat mission. However, a significant challenge raised in this context is how to distribute UAVs efficiently among search and detect tasks within the mission’s constraints. Therefore, the main objective of this project is to propose a system that can be effectively utilized to combat the problem of RPWs where early detection could help win the war against it. To achieve this goal, the project proposes a bio-inspired algorithm to solve the task allocation problem in multi-UAV RPW detect-and-treat missions based on bacterial foraging behavior, which has not been previously introduced to the best of our knowledge. To evaluate the proposed algorithm, a detect-and-treat mission is to be simulated, and a strictly controlled evaluation framework will be followed to examine the efficiency of the system performance and compare it to long-standing task allocation algorithms for multi-UAV missions.