This paper presents the model, solution method, and system developed and implemented for hot rolling production scheduling. The project is part of a large-scale effort to upgrade production and operations management systems of major iron and steel companies in China. Hot rolling production involves sequence dependent setup costs. Traditionally the production is scheduled using a greedy serial method and the setup cost is very high. In this study we propose a parallel strategy to model the scheduling problem and solve it using a new modified genetic algorithm (MGA). Combing the model and man-machine interactive method, a scheduling system is developed. The result of one year's running in Shanghai Baoshan Iron & Steel Complex shows 20% improvement over the previous manual based system. As the company is one of the largest steel companies and the most modernized one in China, the successful application of the scheduling system in this company sets an example for other steel companies which have more potentials for improvement. (C) 2000 Elsevier Science B.V. All rights reserved.