%0 Journal Article %A GAO Rui %A ZHANG Man %A ZHANG Weicun %T Procurement-production-distribution joint scheduling model in job shop environment %D 2019 %R 10.11772/j.issn.1001-9081.2019040712 %J Journal of Computer Applications %P 3383-3390 %V 39 %N 11 %X Aiming at the issue that the Integrated Production and Distribution Scheduling (IPDS) model rarely considers the complex production environment and procurement, the model of Integrated Purchase Production and Distribution Scheduling (IPPDS) with minimizing the order completion time in the job shop environment as target was established and the improved Dynamic Artificial Bee Colony (DABC) algorithm was used to solve the model. Based on characteristics of IPPDS, firstly, to realize the matching relationship between task (processing and transportation) and resource (equipment and vehicle), a coding method of two-dimensional real number matrix was adopted. Secondly, the decoding method based on the process was adopted, and the method to satisfy the constraints for different tasks were designed in the decoding process to ensure the feasibility of the decoding method. Finally, the dynamic coordination mechanism and local heuristic information of leading and following bees were designed in the process of the algorithm. Appropriate parameter intervals of DABC were obtained by experiments, and the experimental results show that:compared with piecewise scheduling and IPDS, IPPDS strategy has the scheduling time reduced by 35.59% and 30.95% respectively. DABC algorithm has the solution effect averagely improved by 2.54% compared with Artificial Bee Colony (ABC) algorithm, and averagely improved by 6.99% compared to the Adapted Genetic Algorithm (AGA). Therefore, IPPDS strategy can meet customer requirements more quickly, and DABC algorithm not only reduces the parameters to be set, but also has good exploration and development ability. %U http://www.joca.cn/EN/10.11772/j.issn.1001-9081.2019040712