Optimization of Operation Sequencing Based on Genetic Algorithm

Process sequencing is considered as the key technology for computer aided process planning (CAPP) and is very complex. This paper deals with optimization of operation sequencing based on Genetic Algorithm (GA) with the lowest cost function. A GA is proposed, including the crossover, mutation operators and selection strategy based on “elitist model”. A matrix of constrants is created based on geometrical shape of part, technology requirements and available machining resources. An optimization of operation sequencing is found through GA in compliance with rules of matrix of constraints. Finally, an experiment is presented to verify that the convergence to optimal solution is better than that to Ant colony optimization Algorithm (ACO)