Allocation of ship maintenance cost based on a hybrid search algorithm of tabu search and annealing particle swarm optimization

According to the ship maintenance structure, the ship maintenance cost can be divided into some parts. Taking the proportions of every part in the gross as independent variables and the ship maintenance cost benefit as explained variable, and a model among the whole benefit of ship maintenance cost and the proportions of every item cost is established through the regress analysis method. Then a hybrid search algorithm which is developed from the simulated annealing particle swarm optimization and tabu search is proposed to find the best allocation policy to obtain the max benefit of ship maintenance cost. And the calculated result shows that the proposed hybrid strategy has the best performance compared with the result obtained by tabu search, particle swarm optimization, and simulated annealing, which is proved by the simulations.