Article ID Journal Published Year Pages File Type
485840 Procedia Computer Science 2012 6 Pages PDF
Abstract

The purpose of this paper is to describe refinements to the recently developed GA-ACO method and to show its application to a real world engineering design problem. The GA-ACO method is a genetic algorithm with a new operator, called an ACO operator. ACO stands for Ant Colony Optimization. The ACO operator uses pheromone trails, a method from Ant Colony Optimization to influence the genetic algorithm. The GA-ACO method is used to optimize an engineering design. Engineers produce a preliminary design for a system using a CAD tool. The output of the CAD tool is then translated into a design graph. Many additional characteristics of the design can be represented by labels on the design graph. The GA-ACO method is then used to optimize these labels. This technique can be applied widely to many design optimization problems. The application considered in this paper concerns optimization of designs for efficient assembly. It uses problems in engineering design encountered at Newport News Shipbuilding, the largest shipyard in the United States. We present a comparison of variations of the GA-ACO method with a standard genetic algorithm for this type of problem.

Related Topics
Physical Sciences and Engineering Computer Science Computer Science (General)