a new method for transportation of in-process products between factories of a supply chain using a hybrid ant colony optimization and simulated annealing algorithm

In this paper, a new method is proposed for scheduling dynamic supply chain systems in the presence of uncertain product demands. the aim of this method is to find the best in-process products scheduling and also the optimum value of outsourcing. in the proposed method both in-site and between-sites in-process products transferring are taken into account. to solve the proposed problem, a hybrid ant colony optimization and simulated annealing algorithm is developed to overcome hardness of the proposed model and then results are compared with a branch and bound and simulated annealing algorithms. the outcomes show that uncertainty in market demands can affect the product scheduling in supply chains. besides, using the proposed method can help determine the best value of using outsource services while the market changes increase. in continue, a new method is developed to control site load variation. the results showed that the proposed hybrid method can provide solutions with better quality.