An improved ant colony optimization （ACO） algorithm is utilized in cell scheduling of the flexible manufaturing process for considering the instrument constraint, manufacturing cost and time. Firstly, the initial we...An improved ant colony optimization （ACO） algorithm is utilized in cell scheduling of the flexible manufaturing process for considering the instrument constraint, manufacturing cost and time. Firstly, the initial weighted directional diagram is set up. Secondly, the algorithm based on the dynamic pheromone updating ensures the quick convergence and the optimal solution, thus improving the feasibility and the stability of the schedule system. Aiming at reducing collaboration with external partners, decreasing the total cost and balancing the production process, the algorithm is efficient in supporting the management process of the manufacturing cell and in strengthening the information arrangement capabitity of the scheduling system. Finally, experimental results of the improved algorithm are compared with those of other algorithms.展开更多
In the flexible job-shop scheduling problem （FJSP）, each operation has to be assigned to a machine from a set of capable machines before alocating the assigned operations on all machines. To solve the multi-objectiv...In the flexible job-shop scheduling problem （FJSP）, each operation has to be assigned to a machine from a set of capable machines before alocating the assigned operations on all machines. To solve the multi-objective FJSP, the Grantt graph oriented string representation （GOSR） and the basic manipulation of the genetic algorithm operator are presented. An integrated operator genetic algorithm （IOGA） and its process are described. Comparison between computational results and the latest research shows that the proposed algorithm is effective in reducing the total workload of all machines, the makespan and the critical machine workload.展开更多
The validity of the ant colony algorithm has been demonstrated as a powerful tool solving the optimization. An ant colony optimization algorithm based on mutation and dynamic pheromone updating in this paper was appli...The validity of the ant colony algorithm has been demonstrated as a powerful tool solving the optimization. An ant colony optimization algorithm based on mutation and dynamic pheromone updating in this paper was applied to settle job shop scheduling problem. Result of computer simulation shows that this method is effective.展开更多
文摘An improved ant colony optimization （ACO） algorithm is utilized in cell scheduling of the flexible manufaturing process for considering the instrument constraint, manufacturing cost and time. Firstly, the initial weighted directional diagram is set up. Secondly, the algorithm based on the dynamic pheromone updating ensures the quick convergence and the optimal solution, thus improving the feasibility and the stability of the schedule system. Aiming at reducing collaboration with external partners, decreasing the total cost and balancing the production process, the algorithm is efficient in supporting the management process of the manufacturing cell and in strengthening the information arrangement capabitity of the scheduling system. Finally, experimental results of the improved algorithm are compared with those of other algorithms.
文摘In the flexible job-shop scheduling problem （FJSP）, each operation has to be assigned to a machine from a set of capable machines before alocating the assigned operations on all machines. To solve the multi-objective FJSP, the Grantt graph oriented string representation （GOSR） and the basic manipulation of the genetic algorithm operator are presented. An integrated operator genetic algorithm （IOGA） and its process are described. Comparison between computational results and the latest research shows that the proposed algorithm is effective in reducing the total workload of all machines, the makespan and the critical machine workload.
文摘The validity of the ant colony algorithm has been demonstrated as a powerful tool solving the optimization. An ant colony optimization algorithm based on mutation and dynamic pheromone updating in this paper was applied to settle job shop scheduling problem. Result of computer simulation shows that this method is effective.
