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Multiple tasks scheduling algorithm for UAV attacking in uncertain environment

The problem of scheduling multiple tasks for Unmanned Aerial Vehicles (UAV) to perform is a NP-hard problem especially in uncertain environment. It is well-known that different scheduling orders for UAV performing multitask will result in different incomes. In accordance, with the characteristics above, this paper proposes a markov state transition tasks scheduling model based on the feature of the task implementation. Then it deduces the cost and income of the task scheduling for acquiring an optimality criterion whose descending order is the optimal scheduling sequence. After that, the optimality of the policy is proved by simulation. Finally we compare our algorithm with the greedy search and the genetic algorithm which shows that the theoretical goal is consistent with the experimental results.