Research On Heterogeneous AGV Fleet Scheduling And Path Planning From The Perspective Of Energy Conservation

With the advancement of the Industry 4.0 process,most manufacturing industries are rapidly transforming into flexible manufacturing and small-batch customized production.Since automated guided vehicle(AGV)can automatically and accurately perform material handling tasks,quickly adjust the transportation and driving routes with the changes of the production process.Therefore,the workshop material handling system composed of multiple AGVs can significantly improve the efficiency of production and manufacturing,thereby enhancing the competitiveness of enterprises.In addition,with the intensification of the global greenhouse effect as well as environment pollution,energy conservation,emission reduction,and sustainable development have become the consensus and transformation goals in the manufacturing field.Based on the above application context and research status,this paper conducts the following research on the energy-saving path planning and scheduling of heterogeneous AGVs fleets in flexible manufacturing workshops:(1)Analyze problems and establish mathematical models.The main characteristics of the vehicle routing problem are expounded,and mathematical models are formulated for the vehicle routing problem of heterogeneous AGV fleets and the green vehicle routing problem with time window constraints.(2)Design and improve genetic algorithms.According to the established mathematical model and the characteristics of the vehicle path planning problem,the genetic algorithm is improved and designed,including the chromosome encoding and decoding method,population initialization,fitness function,and evolution operation of the algorithm,and it is combined with the large-scale neighborhood search algorithm.The specific steps of algorithm solution are formulated.(3)The improved hybrid genetic algorithm is used to solve the specific problem.By testing and solving different examples of the two problems,and verifying the validity and optimization of the proposed model and algorithm,it is analyzed that the use of heterogeneous fleets is compared with the use of traditional homogeneous fleets to carry out loading in the flexible manufacturing workshop.The research results show that compared with the existing solving methods,the improved hybrid genetic algorithm is still competitive in solving the VRPTW in terms of the effectiveness of the algorithm solution;in terms of the optimization of the proposed loading method,compared with using homogeneous light-duty AGV fleet distribution,the driving distance is shortened by 40.4%,compared with the homogeneous heavy-duty AGV fleet distribution method,the total driving energy consumption is reduced by 11.1%.This research provides a solution for solving green heterogeneous AGV scheduling and path planning problems in flexible manufacturing workshops,also provides a reference for solving complex optimization problems using intelligent algorithms.