The issue of scheduling in the supply chain in the minor and operational level in supply chain management is an important issue that has been of interest to researchers. In the classic model of production scheduling, fixed due date of orders (as the input problem) is considered. If the decision is not integrated, the decision on determining the due date and production scheduling decisions for hierarchical are taken, so that after obtaining orders and assign due dates to them (by sales planning department), production scheduling and shop floor operations based on the received sequence is followed. Simultaneous determination due date, and scheduling can lead to lower costs and increase profitability also, in the classic model of production scheduling, traortation department ignored, in other words, production scheduling decisions and decisions related to dispatch planning is done individually, while consolidating decisions can dramatically reduce costs and increase profitability of producers. Integrated due date assignment and production and outbound distribution scheduling (IDAPODS) investigate the integrity between due date assignment and production scheduling and outbound distribution. This Thesis focuses on the integration of the three most important and practical decisions in a supply chain, including the due date assignment, and production scheduling and outbound distribution. The issue under consideration is to minimize the maximum tardiness, due date assignment cost and batch delivery cost. First, to provide solution methods, four mathematical programming models including two mixed non-linear models and two mixed linear models, and a heuristic method to solve it, are presented, After these developments, since the problem is NP-hard and solving real problems on a large scale is virtually impossible, so the three meta-heuristic algorithm for solving the problem presented. Also in this study to evaluate the effectiveness of the development methods, various computational tests have been used, To set the parameters ,Taguchi method, to generate experiments, design of experiments (DOE), and to analyze the results, analysis of variance (ANOVA) was used. The computational results show that heuristic and meta-heuristic methods introduced in this thesis, have high performance also, between developed algorithms, computational results show the superiority of the adaptive genetic algorithm than other methods