Aiming at the uncertainty of marine debris mass in debris collection ship path optimization issue,a ship path robust optimization model is constructed.The model aims to minimize the total cost,which includes transportation cost and fixed cost,meanwhile taking into account constraints such as ship load mass and time window.The uncertainty model is transformed into a deterministic mixed integer programming model through robust equivalence and duality changes,and a hybrid genetic algorithm is designed to solve the model,which combines the mileage saving algorithm,the neighborhood search algorithm and the simulated annealing algorithm.The results show that the proposed model can resist the influence of debris mass uncertainty better.Compared with the traditional genetic algorithm and the simulated annealing algorithm,the total cost of the designed hybrid genetic algorithm decreases by 5.94％and 8.70％,respectively.The sensitivity of uncertainty parameters related to debris mass and carbon tax is analyzed,which provides a reference for decision-makers to formulate appropriate carbon emission policies.
维普
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