The Research And Application Of Path Optimization In Agricultural Machinery Allocation Strategies

With the development of agricultural mechanization,the stock of agricultural machinery in China is growing rapidly.However,the development level of mechanization in different provinces and regions is still unbalanced,so is the demand and supply of seasonal agricultural machinery operation,Cross regional operation of agricultural machinery is still a common occurrence.So a scientific,efficient and low-cost agricultural machinery allocation scheme is to be constructed so as to solve the imbalance of development level between regions of agricultural mechanization and the contradiction between supply and demand of agricultural machinery in operation seasons and to realize the rational allocation of agricultural machinery in cross regional operation.The allocation scheme can not only increase the machinery owners’ income by improving the utilization rate and allocation cost of agricultural machinery and by reducing the allocation cost,but also carries great significance for the development of agricultural mechanization and the modernization of agricultural production.Therefore,this study,taking Heilongjiang reclamation area as the research object,systematically analyzes and summarizes the allocation mode of agricultural machinery in the reclamation area,constructs relevant data models and solution methods,and ultimately comes to the effective solution of the operation relationship allocation model and path optimization model under different allocation modes of agricultural machinery based on intelligent optimization theory and method,which effectively solves the problem of rational and efficient allocation of agricultural machinery in cross regional operation of agricultural machinery.(1)According to the demand of scientific allocation of agricultural machinery,through systematic investigation,summary and analysis,three allocation modes of agricultural machinery in Heilongjiang reclamation area are summarized,that is,the "unified allocation mode inside and outside the farm",the "on-site priority allocation mode" and the "Allocation mode based on urgent tasks".The "unified allocation mode inside and outside the farm" is constructed to maximize the owners’ income by way of grabbing the cross regional market;the "on-site priority allocation mode" is implemented to ensure the sufficient reservation of agricultural machinery for the completion of internal farm operation within the specified time,the rest of which is allocated outside the site for cross regional operation.The "allocation mode based on urgent tasks" aims to make a reasonable arrangement of agricultural machinery operation allocation and of route optimization under emergency tasks to ensure the shortest total operation path of agricultural machinery operation and the tasks completion within the shortest time.(2)According to the characteristics of “unified allocation mode inside and outside the farm”,“on-site priority allocation mode” and the "allocation mode based on urgent tasks",the agricultural machinery allocation problem is abstracted into agricultural machinery operation relationship allocation model and allocation path optimization model,and the corresponding solution method is constructed based on improved genetic algorithm.A hybrid coding multi offspring genetic algorithm is proposed.The roulette selection method based on order combined fitness function is combined with L é vy mutation operator and binary coding site mutation strategy,which is used to effectively solve the operation relationship model of agricultural machinery;a sequential coding genetic algorithm is constructed.By combining sequential crossover and two exchange heuristic crossover,the crossover operator is constructed,an adaptive constant C from large to small is designed,and a random number r evenly distributed between [0,1] is randomly generated.When r ≤C,the sequential crossover operator is selected;otherwise,two exchange heuristic crossover operators are selected.At the beginning of genetic algorithm iteration,the combinatorial crossover operator can select the sequential crossover operator with high probability;in the later stage of iteration,the combinatorial crossover operator can select two exchange heuristic crossover operators with high probability.(3)In order to verify the effectiveness of the proposed hybrid coding multi-generation genetic algorithm and the genetic algorithm of sequential coding in solving the problem of agricultural machinery path optimization,the agricultural machinery used in the soybean harvesting operation of Jianshan farm in 2020 and the problem of agricultural machinery in different allocation modes was tested and the optimal agricultural machinery allocation plan and the optimal transportation route of each agricultural machinery are thus given as the solution.On this basis,the total income from soybean harvesting operations of different allocation schemes is compared with the actual convergence of Jianshan farm in 2020.The analysis results show that the income obtained from soybean harvesting operations in the optimized allocation scheme is significantly higher than the actual income,which verifies the effectiveness of the proposed method for solving the agricultural machinery allocation problem.(4)In order to effectively popularize and apply the research results in the real agricultural machinery allocation,the agricultural machinery allocation management information system is designed and implemented,which effectively integrates a series of basic information management of the users,the field,the agricultural machinery and of the agricultural machinery allocation management as well as the output information comprehensive information inquiry report.The development and application of the management information system constructs a unified management platform for basic information of farmers,farmland and agricultural machinery,offering a rapid and real-time solution to agricultural machinery allocation operation relationship and path optimization based on improved genetic algorithm.The optimization path scheme will provide decision support for agricultural machinery management departments and agricultural machinery households to choose rational agricultural machinery allocation scheme.