关键词: 布局问题, 解空间编码, 遗传算法, 空间自动规划

Abstract: To solve layout problems in complex structures of products, through improvements on the real-coded genetic algorithm, a Solution-Vector Coded Genetic Algorithm (SVCGA) was proposed. In the SVCGA, the variables of target function were regarded directly as genes of chromosomes and were coded. To solve layout design problems by SVCGA, the problems pretreatment was necessary in the process of SVCGA evolution. Firstly, the idea of Simulated Annealing Algorithm (SAA) was introduced to select operator to control individual diversity. Then, different cross and mutating operators were acted on different variables. Moreover, to control the search range of the algorithm, a fluctuant scale was multiplied to the continuous variables before they were mutated. Finally, the result of each generations evolution was managed according to the strategy of preserving the elitist. Through SVCGA，the automated spatial planning has been achieved in three-dimensional layout problems. In addition, to test the feasibility and effectiveness of SVCGA, a two-dimensional and a three-dimensional layout problem were introduced and solved by SVCGA. The layout results indicated that SVCGA was feasible and effective.

Key words: layout problems, solution-vector coding, genetic algorithm, automated spatial planning