The Evolutionary Algorithms For Solving Placement Problem

Two-dimensional placement problem arises from a variety of situations including apparel industry, parts nesting problems and Super Large-Scale Integration (SLSI). The placement result has an important impact on the qualities target in profession production, for example rationalization, economical security, etc. And the placement process is also the optimum one. Placement problem belongs to aggregate optimum problem and it is NP complete problem. Though after the hard work, by far there is not mature theory and practical significance. Evolution calculation is the evolution process which imitates the nature by computer, especially the evolution process of life to solve complicated problem. In these methods of settling optimum problem, evolution calculation is a vigorous instrument. Evolution calculation is the evolution process which imitates the mature by computer.Genetic Algorithm (GA) is a searching algorithm that is based on the evolution theory and principles of genetics of bloscience. Three operators (crossover replication mutation) are used in two- dimensional placement problem. Many parent generations make many filial generations, and then the individual will be abandoned according to the value of the objective function.In this paper, by improving the method for placing rectangle based on placement points, we present the Estimation of Distribution Algorithm for two-dimensional placement problem. Test results show that EDA is better than Genetic Algorithms.