VLSI floorplan optimization problem aim to minimize the following measures such as, area, wirelength and dead space (unused space) between modules. This paper proposed a method for solving floorplan optimization problem using Genetic Algorithm which is named as ‘Lion Optimization Algorithm’ (LOA). LOA is developed for non-slicing floorplans having soft modules with fixed-outline constraint. Although a number of GAs are developed for solving VLSI floorplan optimization problems, they are using weighted sum approach with single objective optimization and crossover between two B*tree structure is not yet attempted. This paper explains, power of B*tree crossover operator for multiobjective floorplanning problem. This operator introduces additional perturbations in initial B*tree structure to create two new different B*tree structures compared with classical GA approach. Simulation results on Microelectronics Center of North Carolina and Gigascale Systems Research Center benchmarks indicate that LOA floorplanner achieves significant savings in wirelength and area minimization also produces better results for dead space minimization compared to previous floorplanners.

VLSI平面图优化问题旨在最小化以下措施，例如面积，线长和模块之间的死空间（未使用的空间）。本文提出了一种使用遗传算法解决平面布置图优化问题的方法，称为“狮子优化算法”（LOA）。LOA针对具有固定轮廓约束的软模块的非切片平面图而开发。尽管为解决VLSI布局优化问题而开发了许多GA，但它们仍使用具有单目标优化的加权和方法，尚未尝试在两个B * tree结构之间进行交叉。本文解释了B * tree交叉算子对多目标平面规划问题的影响。与经典GA方法相比，该算子在初始B * tree结构中引入了其他扰动，以创建两个新的不同B * tree结构。在北卡罗来纳州微电子中心和Gigascale系统研究中心的基准测试结果表明，与以前的平面规划器相比，LOA平面规划器在节省电线长度和最小化面积方面也取得了显着的节省。