ANT-Q algorithm based optimization approach for process planning

This paper presents a method for the process planning of prismatic part, where the machining operations of a manufacturing feature can be done by different machine, set-ups, and tools. The optimization objective is to minimize the total cost which includes the Preparing Cost and the Machining Cost. Here, process planning is modeled as a constraint-based traveling salesman problem (TSP), and an ant colony algorithm is developed and embedded in the optimization algorithm. A case study and comparisons with the genetic algorithm approaches show that the ant algorithm can significantly reduce the machining cost and be better.