Ant Colony Algorithms For Solving Order Acceptance And Scheduling

For a make-to-order industry, due to the production capacity limitation, delivery commitment and other factors, accepting and scheduling all the orders may result in beyond delivery time,appearing delay penalty and dropping customer satisfaction. From the view of the supply chain,we should distinguish the importance of different orders for enterprise, cooperate and coordinate order acceptance and scheduling decision-making, to realize optimized enterprise profit.Order acceptance and scheduling optimization decision problem is typical NP-hard. It is difficult to use the traditional optimization algorithms to solve the large-scale problems. Ant colony algorithm is by Italian scholars Dorigo. He was inspired by the natural real ants foraging process. From the practice we can see the ant colony algorithm has more applications in complicated combinatorial optimization problems. This paper introduces the two different environment:single environment and the two machine flow shop. And for the single environment we designed the improved ant colony algorithms. In the improved ant colony algorithm we make properly modifications for the probability function which can help select the order of high revenue, emergency delivery. A variety of local search can effectively jump out of local convergence. Second, for the two machine flow shop, we designed hybrid ant colony algorithms which combined tabu search algorithm with ant colony algorithms. Ant colony algorithms can provide a good initial solution for tabu search algorithm, and tabu search algorithm can enhance the local search ability for ant colony algorithms, so greatly enhance the performance of optimization ability.Finally, we design two kinds of environment of ant colony algorithms and do a lot of simulation experiments. The results show that the improved algorithms have good performance both in the result of the operation and operation time.