Ship Speed Optimization Based on Multi-objective Particle Swarm Algorithm

doi:10.16182/j.issn1004731x.joss.17-0111

Abstract

Abstract: Ship speed optimization is an effective means to reduce operational costs in the downturn of shipping. To deal with the conflict between reducing the operating cost and reducing the ship emissions, the multi-objective ship speed optimization model is proposed based on the influence of the actual wind and wave. The MOPSO algorithm is introduced to solve the Pareto optimal solution set, and the compromise speed is an effective tradeoff based on the improved TOPSIS algorithm. The operational shipping route is selected as an example to simulate and verify the model. The results show that the operating costs and ship emissions at the optimal speed are consistent with the measured data. The optimization model can effectively reduce the emission and control the operation cost, and the algorithm is proved to be effective.

Key words: ship speed optimization, multi-objective particle swarm optimization (MOPSO), TOPSIS algorithm, cost, emission

CLC Number:

U697.1

Zhang Jinfeng, Yang Taoning, Ma Weihao. Ship Speed Optimization Based on Multi-objective Particle Swarm Algorithm[J]. Journal of System Simulation, 2019, 31(4): 787-794.

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