A Directional Heuristics Pulse Algorithm for a Two Resources Constrained Shortest Path Problem with Reinitialization

Abstract

<p style='text-indent:20px;'>In this paper, the path planning problem of UAV flight error correction is studied, and a mixed-integer linear programming (MILP) model is proposed to solve the resource constrained shortest path problem (RCSPP-R) with reinitialization, and its resource accumulation can be reinitialized to zero at the reset node. Since RCSPP-R is a NP-hard problem, Pulse algorithm is used to solve the proposed model. Aiming at the high computational cost of pulse algorithm, three pruning strategies are proposed to improve the effectiveness and efficiency of the algorithm, namely, preprocessing strategy based on direction constraint to reduce the search space, dynamic relaxation strategy to improve the quality of boundary, and heuristic search strategy to optimize the node expansion sequence. Then the time-consuming of the algorithm and the number of dominant solutions are used as evaluation indexes for comparison. Numerical results show that the proposed algorithm can deal with this problem more reliably. Specifically, compared with the Label Correction algorithm, the original Pulse algorithm and the Ant Colony algorithm, there are advantages in the number of superior solutions, and compared with the above three algorithms, the time consumption is reduced by 31.64%, 88.52% and 83.5% respectively.</p>