Multi-objective Intelligent Optimization Algorithm Research On Steel Cutting Problem

Steel cutting problem in in building engineering are widely used, to solve the problem of the steel cutting, Can improve the utilization ratio of steel, saving production cost, improve efficiency, thus the enterprise to improve efficiency and enhance its competitiveness. So about the study of steel cutting is attentioned more and more by enterprise.About construction project in reinforced cutting and steel structure rectangular pieces arrangement, this paper Application intelligent optimization algorithms such as evolutionary algorithm and simulated annealing algorithm to study them. In an attempt to meet the construction and design requirements, determine the optimal material plan, the maximum extent save steel, reduce the waste.Main contents are as follows:1. Steel bar cutting problem(1) According to the theory of multi-objective genetic algorithm,a multi-objective reinforce optimization methods based on pareto is proposed. Reinforced utilization and user need two index was as next makings optimization goal. Using the decimal type coding, cutting model number and repetitions constitute paired gene composition chromosomes and Pareto compete method was introduced to choose operation. According to this algorithm developed reinforced material optimization program. Numerical results show that the proposed method can satisfy customer needs, under the premise of the best possible r.c. utilization, and can also provide multiple optimal solutions for the user according to the actual conditions and personal preference for choice.(2) A new adaptive genetic simulated annealing algorithm was proposed for improving search effect evolutionary algorithm. Dynamic crossover rate and dynamic mutation rate is designed to enhance convergence. Meanwhile, annealing operation is joining in the crossover operator and later made algorithm in later evolution has strong "climbing" performance. Numerical calculation shows that compared with the traditional genetic algorithm, the proposed algorithm improved evolution speed and local search capability.2. Steel structure rectangular plate arrangement problems On the analysis of the strip layout problem of rectangular pieces of optimization based on the characteristics of the mathematical model, the mathematical models were set up, and describes some common optimization algorithm and arrangement algorithm. In a certain constraint conditions, using genetic simulated annealing algorithm method to strip layout problem of rectangular pieces of the optimal solution and the results are compared and analyzed. In this paper, the genetic simulated annealing algorithm combined with improved minimum horizon of the search algorithm for the strip layout optimization of rectangular pieces, generate layout results meet in the process of production of steel structure into technological requirements , The utilization ratio of steel about 94% , can be applied to the practical production enterprise.