The Vessel Routing Optimization For Marine Debris Collection

Marine debris refers to the solid waste in the sea and beach.Nearly 80 percent of marine debris comes from land sources.More and more individuals and organizations are aware of the harmfulness of debris,which is one of the most common pollution problems affecting the environment and human beings.The influence of food chain caused by marine debris is fatal to the living environment and survival of marine life and even human beings.However,there are few researches on the recycling and treatment of marine debris.Therefore,how to effectively deal with marine debris and to formulate a reasonable recovery plan is the focus of this paper.Since the location of marine debris is not fixed,we first apply the General NOAA Operational Modeling Environment(GNOME)software to predict the trajectory of marine debris and determine its location.Then,use the logistics network to optimize the collection of marine debris.For the path planning of debris collection,a mixed-integer linear programming model is proposed that aims at minimizing operating costs,while focusing on debris points weight,operating time window,and vessels fuel loading constraints.The model takes into account the piecewise linear function model of fuel consumption related to the vessel’s deadweight,and proposes a hybrid adaptive large-scale neighborhood search algorithm for the problem.Using the ALNS algorithm as the framework,a targeted design is made from the goal.Remove-insert operator based on weight order index and fuel consumption.In addition,drawing on the local search idea of ??wolf pack algorithm,a tree search mode is proposed to adjust the range and density of neighborhood search.This paper takes the East China Sea estuary of the Yangtze River as an example to test the proposed model and algorithm.It is verified that the designed algorithm is feasible and the solution efficiency is high.In addition,in the analysis part of the calculation example,the degree of impact of the timing of the recovery operation on the operation cost is analyzed,and the importance of choosing the timing of the recovery operation is explained.Through the sensitivity analysis of debris weight and vessel capacity,it is found that the influence of the weight change of debris points on the planned route is closely related to the vessel model and initial weight.At the same time,choosing the appropriate vessel model according to the weight of debris can improve operation efficiency and greatly reduce Operating cost.Secondly,the issue of discrete speed selection of vessel is considered,that is,the vessel chooses low speed,medium speed or high speed according to the demand among the various voyages.On this basis,a two-objective mixed integer programming model is established.The objective functions are to minimize operating time and minimize carbon emissions.The maximum cost budget is added to the constraints.Aiming at the problem of bi-objective optimization and speed selection,a pheromone-guided adaptive large-scale neighborhood search algorithm based on the AMOSA algorithm is proposed.The algorithm uses the AMOSA algorithm as the multi-objective judgment update standard for the population,and the ALNS algorithm as the population neighborhood search mechanism.The insertion operation combines the pheromone-guided selection speed level method,and then introduces the concept of priority to determine the best insertion method.Finally,an example is used to verify the effectiveness of the improved algorithm.Under the premise of dual goals,the influence degree of the best time for the vessel to perform operations is explored and the sensitivity analysis of the speed range of the vessel’s speed is carried out.