Research On Loading Problems About Castings Of Heat Treatment In Furnace Based On Hybrid Genetic Algorithm

Heat treatment furnace scheduling is an incompatible casting scheduling problem under complex constraints,and it is an important part of the production planning of foundry enterprises.To solve the problem of intelligent scheduling of heat treatment of castings,in the early stage,the research group proposed the planning model of the heat treatment furnace of the foundry and calculated its solutions,then make the algorithm-assisted scheduling mode of the heat generation plan realized,which achieved good application results.However,only the weight of the heat treatment furnace is considered in the modeling,but the shape and size of the casting are not considered,which makes it difficult to load the calculated furnace batch castings into the furnace.Moreover,the manual arrangement of the charging scheme often does not make good use of the heat treatment furnace,which reduce the efficiency of the heat treatment workshop's production.In this thesis,a three-dimensional mathematical model of heat treatment castings charging is established.Using cuboid element to fit the castings,the charging scheme of heat treatment castings for specific batches is studied,and an effective hybrid genetic algorithm is proposed.Firstly,the status quo of the three-dimensional bin-packing problem is analyzed,and the mathematical model of multi-objective and multi-constraint charging is established.Combining with the actual furnace loading situation of enterprises,this thesis put forward the model assumption,considered nine kinds of furnace loading constraints,such as rotation constraints,volume constraints,top prohibition of stacking and bottom prohibition of stacking and established the objective of maximizing the space utilization ratio and remaining effective space of heat treatment furnace,which is the model foundation for solving the three-dimensional charging problem in furnace.Secondly,a step-by-step solution of heat treatment casting charging based on hybrid genetic algorithm is proposed.The solution scheme divides the original problem into two stages,in the first stage,work pieces are compounded into combinatorial blocks based on heuristic algorithm,and a list of candidate feasible blocks is generated.In the second stage,work pieces loading order and placement state are used as real genetic codes,and adaptive crossover operator and adaptive mutation operator are set up for three-dimensional stoving problem.Using both heuristic algorithm and genetic algorithm,the search for approximate optimal solution of the problem in encoding space is completed.Finally,an experiment based on standard examples and actual data of enterprises is designed to verify the effectiveness of the algorithm.On this basis,a software for the three-dimensional loading problem in furnace is developed.Based on seven standard examples,the proposed hybrid genetic algorithm is compared with heuristic algorithm,single genetic algorithm and hybrid simulated annealing algorithm.The results show that the proposed hybrid genetic algorithm has obvious advantages in the comprehensive performance of filling rate,convergence speed and algorithm accuracy.At the same time,a typical foundry enterprise in China was selected as the research object.The heat treatment charging workshop of the enterprise was investigated on the spot.The dimension data of the production work pieces was excavated and applied to the simulation data.The loading results were calculated.Based on the OpenGL graphics library and the development framework of the QT interface,a three-dimensional charging software was developed.The results show that the software can effectively determine whether a specific batch of heat treatment work pieces can be loaded into the furnace.Compared with the manual arrangement of the furnace loading scheme,this algorithm can help arrange the furnace loading scheme to improve the space utilization of heat treatment furnace equipment,thereby improving the production efficiency of the heat treatment workshop.