Dynamic Air Defense Resource Allocation Optimization Based on Improved Differential Evolution Algorithm
Based on the integrated performance of weapon equipments such as radars,launchers and missiles,a mixed-integer decision model that minimizes the total target intercept value and the probability of survival based on Target-Set,Resource-Set is developed.A new improved differential evolutionary algorithm has been introduced to solve the problem,and the initial solutions is generated by using the reverse learning strategies to ensure the quality of the initial populations.An inspiration rule for the fast repair and reconstruction is designed to work at multi-stage to improve the search capability of the algorithm.The simulation experiment results show the algorithm's superiority in search time and search accuracy,which can maintain the efficient combat capabilities and decision-making under the random influence of dynamic events.
air defense operationsdynamic air defense resource allocationopposition-based learningimproved differential evolution algorithm
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