Study On Fibre's Furniture Large-Scale Cutting Stock Problem Based On Genetic-Simulated Annealing Algorithm

Cutting stock is concerned with how to saving material, optimize resources in product designing, manufacturing. The research on the problem has important economic meaning and social benefit. It is very complicated and difficult in computing theory, but it has got the extensive application in the actual manufacture. With the development of intelligent optimize algorithm theory and computer technology, it offers the possibility to people to solve the problem with modern optimal algorithm and computer. In this paper, the cutting stock problem was consistsed of packing rectangular items onto a rectangular raw material in the fibre furniture manufacture.Considered of the concrete characteristics of the cutting stock problem in the fibre furniture, it combined the craft and restraint condition in the fibre furniture, it gave the definition, characteristics and nature of cutting stock in rectangle parts on the rectangle raw material board, and had put forward the restrained of craft and items' scale modes of the fibre furniture, the mathematics model was given; On the research of cutting stock algorithm, the paper presented a method of "Be Feasible on Producing". According to the craft characteristic of "Guillotine cutting" in the fibre furniture manufacture, the paper adopted the binary tree structure to perform the process with layout pattern, ensureed that all schemes were feasible while producing. It made the whole solutions feasible while the cutting patterns were generated, so that it avoided carrying on feasible verification to encode in the course of searching optimal solution; The paper presented the application of modern intelligent optimizing algorithm: Genetic Algorithm (GA), Simulated Annealing (SA), and hybrid algorithm according to each advantages of Genetic Algorithm and Simulated Annealing (GASA) in the fibre furniture cutting phase, and in the course of applying, the paper improveed the algorithm; To the question of the difficulty in determining the proper cooling schedule and choosing a proper neighborhood in simulated annealing algorithm, and also the difficulty of escaping from the local optimal solution, the paper designed a temperature controlled cooling schedule, local optimum judging function and temperature raising function was given, it raised temperature in time after the search entered the local optimal solution, and it could make searching escape from the local optimal solution, ensured the final solution to be the optimal. It designed initial temperature, neighborhood structure and random acceptive function, the paper improved the speed of solving process; To the question of characteristic of Genetic Algorithm applied in the rectangular cutting stock problem, the paper presented a kind of Objective Oriented genetic coding method. It proposed the genetic mutation scheme on the basis of " Run-Through Material", unused gene quantity had been brought down to zero after making a variation, and it put forward corresponding definite method and key points, fitness function, initial formulation and genetic operation; The paper carried on detailed comparing and analysis to the two algorithms mentioned above, summarized the advantages and deficiencies in terms of the theory and the implementation of the two algorithms, fetched the advantages of Simulated Annealing algorithm and Genetic Algorithm, combined them together well, included the temperature controled ofSimulated Annealing algorithm and the coding method and the way of variation of Genetic Algorithm, that made the ability of searching for the optimum of the new hybrid algorithm: Genetic-Simulated Annealing algorithm to be improved greatly; The paper compared and analyzed the three kinds of algorithms in terms of theory and practice, Genetic-Simulated Annealing algorithm had not only such operation of individual, mating, gene, heredity, making a variation etc. in Genetic Algorithms, but also had Simulation Anneal algorithm's temperature controling, cooling schedule and technology of accepting probability etc. too, it could get the large scale rectangular cutting's best solution faster.The paper developed the fibre furniture manufacture's large scale rectangular cutting stock system, the experiment showed that the optimization result of the sysytem is higher than the domestic similar research results, and it was extremely simple and convenient to operate, it was remarkable to economize the raw materials, and it was practicability. To solve the same group data, the third method (Genetic-Simulated Annealing) is more efficiency.