Research And Application Of Furniture Board Packaging Algorithm

Furniture board packaging is the most important part of the transportation process of furniture board.It refers to the condition under certain constraints,such as the area utilization of each layer in the package,the space volume utilization,the height limit of the board in the package,the weight limit,and the center of gravity.Constraint,etc.,a rectangular board having a certain length,width and height is reasonably loaded into the loading box.Furniture board packaging is a typical multi-constrained optimal combination problem,and this type of problem is also called NP-hard.Classic NP-hard problems include container loading problems,TSP problems,and vehicle scheduling issues.The problem of furniture board packing is to improve the overall load capacity utilization of the board loading box and reduce the number of loading boxes to reduce the cost of cargo transportation,which is of great significance to today's rapidly growing furniture industry.Because the NP-hard problem is very complicated and of great application value,it has become the focus of academic research today.In recent years,many classical optimization combination algorithms have been proposed by the academic community to solve NP-hard problems,such as ant colony algorithm,simulated annealing method,distributed estimation algorithm,dynamic programming method,genetic algorithm,etc.However,due to realistic constraints and cargo combinations The diversity,single optimization combination algorithm can not solve such problems well.Aiming at the above problems,this paper proposes a cascade optimization combination algorithm based on heuristic algorithm and hybrid genetic algorithm.The pre-stage uses a heuristic algorithm based on manual packing experience to obtain a high-quality packing solution,and iteratively mutates the solution as the initial population of the post-mixing genetic algorithm until the optimal solution of the problem is searched.In this paper,the tabu search algorithm with strong local search ability is used as the mutation operator of traditional genetic algorithm to form a hybrid genetic algorithm,which overcomes the shortcomings of traditional genetic algorithm with weak local search ability and easy precocity.Secondly,heuristic algorithm is used as hybrid genetic algorithm.Provide a better quality initial solution to improve the convergence speed of the algorithm.Therefore,the cascade algorithm proposed in this paper not only obtains high quality of the solution but also has higher execution efficiency than the general algorithm.The first chapter of this paper details the research background and significance of the paper and the research status at home and abroad.The second chapter summarizes the problem of furniture board packaging,explains the commonly used algorithms of current item loading problems and analyzes the advantages and disadvantages of each algorithm.The chapter describes the constraints of furniture board packing,establishes the corresponding mathematical model according to the optimization objectives and constraints,and designs the heuristic algorithm of the pre-stage algorithm.The heuristic loading strategy is deeply designed.The chapter ends with the heuristic algorithm.The furniture board data is processed to obtain the packing result and analyzed.The fourth chapter analyzes the traditional genetic algorithm and the tabu algorithm,and combines their respective characteristics to propose the hybrid genetic algorithm of the post-stage algorithm,focusing on the hybrid genetic algorithm.The parameters are designed and the algorithm execution steps are formulated.The algorithm is used to analyze the experiment.The fifth chapter combines the heuristic algorithm with the hybrid genetic algorithm as the cascade algorithm to improve the related parameters in the cascade algorithm and use the string.Level algorithm for processing furniture board data,resulting in a package The results were compared with the previous algorithm;Finally,the paper summarizes and prospects.Through a large number of furniture board packaging data processing,a comparative analysis of various algorithms,it can be concluded that the cascading algorithm combined with the heuristic algorithm and the hybrid genetic algorithm proposed in this paper effectively improves the furniture board loading compared with the traditional algorithm.The quality of the box and the efficiency of the algorithm are very practical for the furniture board packing operation,and also have a good reference for the same boxing problem.