Title: Modelling and realisation of multi-sensors mission planning problem based on fuzzy chance-constrained bi-level programming in anti-TBM combat
Authors: Peng Ni; Gang Wang; Jin-Mang Liu; Cheng-Li Fan
Addresses: School of Air and Missile Defense, Air Force Engineering University, Xi'an, China ' School of Air and Missile Defense, Air Force Engineering University, Xi'an, China ' School of Air and Missile Defense, Air Force Engineering University, Xi'an, China ' School of Air and Missile Defense, Air Force Engineering University, Xi'an, China
Abstract: The Multi-Sensors Mission Planning (MSMP) optimisation model based on Fuzzy Chance-Constrained Bi-Level Programming (FCCBLP) is presented on the basis of analysing the deficiency of the existing MSMP model in anti-TBM combat. Firstly, employing the mission reliability and detecting advantage as the upper and the lower objective function of the model based on taking the model constraints in complex battlefield environment into consideration, respectively. Secondly, particle coding scheme with hierarchical structure for multi-constrained bi-level MSMP problem is constructed. On this basis, an Improved Fuzzy Particle Swarm Optimisation (IFPSO) algorithm is proposed with fuzzy simulation technique and cloud self-adaptive mutation operator. Finally, the simulation results show that the proposed algorithm has a strong global searching ability and fast convergence speed which meet the high requirements about the timeliness of the large-scale MSMP problem.
Keywords: multi-sensor mission planning; multiple sensors; fuzzy chance-constrained bi-level programming; cloud computing; self-adaptive mutation operators; fuzzy PSO; particle swarm optimisation; complex environments; battlefield environments; TBM combat; fuzzy simulation.
International Journal of Wireless and Mobile Computing, 2015 Vol.9 No.2, pp.177 - 191
Received: 08 Jun 2015
Accepted: 24 Jun 2015
Published online: 19 Oct 2015 *