LAV Path Planning by Enhanced Fireworks Algorithm on Prior Knowledge

Abstract

Path planning plays an extremely important role in the design of LAVs (Loitering Air Vehicles) to accomplish the air combat task fleetly and reliably. The planned path should ensure that LAVs reach the destination along the optimal path with minimum probability of being found and minimal consumed fuel. Traditional methods tend to find local best solutions due to the large search space. So it takes a lot of time and consumes a lot of computing resources. In this paper, a new young intelligent algorithm-fireworks algorithm is introduced, and EFWA (enhanced fireworks algorithm)-its enhanced version is used to find the optimal solution. At the same time, the battlefield prior knowledge is fully utilized to predict the existence space of the potential optimal trajectory. Greatly the search space reduced, plan planning efficiency is significantly improved. Path planning method effectiveness in this paper has further been improved compared with FACPSO. Moreover, the EFWA on prior knowledge performs well on the application of dynamic path planning when the threats cruise randomly than FAC-PSO.

A novel Fireworks Algorithm with wind inertia dynamics and its application to traffic forecasting

“…Other modifications to the initial FWA and to the later contributed EFWA include adaptive amplitude calculation [8], cooperation among fireworks [9] or dynamic adjusting of parameters to balance exploitation and exploration [10]. Aside from performance improvements, applications of fireworks algorithm 978-1-5090-4601-0/17/$31.00 c 2017 IEEE to real optimization scenarios are yet scant [11], [12], [13], [14], [15] due to the relative youth of this heuristic. A practical application of interest within the scope of this work is [16], where FWA is used to optimize the parameters of a spam detection algorithm.…”