Nowadays, the growing complication in the productive industries and need for more efficiency, utilization of production cycle modern technology, more flexibility, better quality of productions, better satisfying of the customer's expectations and lower costs, have been changed the production appearance. In the steel industry that involves with large amount of wealth, labor and energy flow a small improvement in planning has significant consequences such as reducing costs, energy consumption, production time, delivery time and also increasing customer satisfaction. This research aim to present a efficient model in order to schedule the orders in the product line of cold rolled in the "Esfahan's Mobarakeh Steel Company" so that beside the decreasing the inventory level and optimum usage of production line, the costs of delays will be decreased that cause to uplifting of the reputation of the company. In this study, in addition to providing production planning methodologies in different areas of the industry, three models of planning and scheduling orders in cold rolling area with regard to possible output of hot rolling is presented. The first model is a multi-objective planning model which minimizes the costs of delays, inventory keeping and line shutting down. The second model is a linear programming model which has two general cases. This model can be applied in industries like aluminum, copper, textile, carpet weaving, dyeing and generally in each industry that has a multi-stage multi-product production flow. According to certain features of steel industry such as high number of orders, weakness of software in dealing with these orders and other technological constraints, the third model is presented which is a Mixed Integer Linear Programming. In the case that the number of variables is very high and the computer cannot respond in an acceptable time, a heuristic algorithm to improve the initial solution from the third model (without limitation zero and one) is presented The third model is solved by applying real data of Mobarakeh Steel cold rolling in two stages. At first the third model without considering zero-one constraint is solved. In what follows, the zero-one and some other constraints obtained from heuristic algorithm are added to the model and the model is solved by GAMS 23.5.2_win32 software. All the computations are implemented on computer with 32GB RAM and CPU 2.93GHz. The optimal solution, i.e. the required amount of production of each product on each machine per day in three months time horizon is obtained. The output plan demonstrates a remarkable reduction in the volume of delayed orders and also in unused capacity in machineries.