Case-Based Reasoning Genetic Algorithm for Rectangle and Circle Packing Problem with Equilibrium Constraints

Abstract

The circle and rectangle packing problem with equilibrium constraints is difficult to solve in polynomial time. In this paper a case based reasoning genetic algorithm is presented to improve its solving efficiency and accuracy. Its main idea is that the initial population of genetic algorithm consists of the reasoning solutions attained from the case-solutions and its non feasible layout solutions generated randomly; in each iteration step of the evolutionary process, a non-isomorphic layout pattern solution of the current optimal individual is constructed automatically and replaces the worse one in the population. The experimental results demonstrate that the proposed algorithm has higher computational speed and accuracy than HCIGA.