Optimal Scheduling Method of Marine Transportation Resources Based on Wolf Swarm Algorithm

Sun, Y.; Wu, H., and Zhan, R., 2019. Optimal scheduling method of marine transportation resources based on wolf swarm algorithm. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 646–651. Coconut Creek (Florida), ISSN 0749-0208. In order to effectively reduce the cost and completion time of resource scheduling, an optimal scheduling method for marine transportation resources based on wolf swarm optimization is proposed. In order to expand the theoretical system and practical application of wolf swarm optimization, aiming at a series of shortcomings existing in wolf swarm algorithm, the wolf swarm method is optimized in the following two aspects: the first is to improve the internal operation mechanism to develop the performance of wolf swarm algorithm in solving single-objective optimization, multi-peak optimization and multi-objective optimization problems; the second is to introduce other mechanisms, which are integrated into the optimization strategy of the wolf swarm algorithm, so that the algorithm has the ability to deal with multi-peak and multi-objective optimization problems. The optimal scheduling of maritime transportation resource is abstracted into the Travelling Salesman Problem (TSP) problem. The improved wolf swarm algorithm is used to solve the TSP model, and the optimal solution of the TSP model is obtained to realize the optimal scheduling of maritime transportation resource. The simulation results show that the proposed method can effectively reduce resource scheduling costs and task completion time.