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A mathematical programming model and solution for scheduling production orders in Shanghai Baoshan Iron and Steel Complex

机译:上海宝钢股份公司生产订单调度的数学规划模型和求解

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In this paper, we investigate the production order scheduling problem derived from the production of steel sheets in Shanghai Baoshan Iron and Steel Complex (Baosteel). A deterministic mixed integer programming (MIP) model for scheduling production orders on some critical and bottleneck operations in Baosteel is presented in which practical technological constraints have been considered. The objective is to determine the starting and ending times of production orders on corresponding operations under capacity constraints for minimizing the sum of weighted completion times of all orders. Due to large numbers of variables and constraints in the model, a decomposition solution methodology based on a synergistic combination of Lagrangian relaxation, linear programming and heuristics is developed. Unlike the commonly used method of relaxing capacity constraints, this methodology alternatively relaxes constraints coupling integer variables with continuous variables which are introduced to the objective function by Lagrangian multipliers. The Lagrangian relaxed problem can be decomposed into two sub-problems by separating continuous variables from integer ones. The sub-problem that relates to continuous variables is a linear programming problem which can be solved using standard software package OSL, while the other sub-problem is an integer programming problem which can be solved optimally by further decomposition. The subgradient optimization method is used to update Lagrangian multipliers. A production order scheduling simulation system for Baosteel is developed by embedding the above Lagrangian heuristics. Computational results for problems with up to 100 orders show that the proposed Lagrangian relaxation method is stable and can find good solutions within a reasonable time. (c) 2006 Elsevier B.V. All rights reserved.
机译:本文研究了上海宝山钢铁总公司(宝钢)的钢板生产中的生产订单调度问题。提出了确定性的混合整数规划(MIP)模型,用于在宝钢某些关键和瓶颈工序中安排生产订单,其中考虑了实际的技术约束。目的是确定在能力限制下相应操作的生产订单的开始和结束时间,以使所有订单的加权完成时间之和最小。由于模型中存在大量变量和约束,因此开发了一种基于拉格朗日松弛,线性规划和启发式算法的协同组合的分解解决方案方法。与常用的放宽容量约束方法不同,此方法还可以放宽将整数变量与连续变量耦合的约束,这些约束由拉格朗日乘数引入目标函数。通过将连续变量与整数变量分开,可以将拉格朗日松弛问题分解为两个子问题。与连续变量有关的子问题是一个线性规划问题,可以使用标准软件包OSL来解决,而另一个子问题是一个整数编程问题,可以通过进一步分解来最佳地解决。次梯度优化方法用于更新拉格朗日乘数。通过嵌入上述拉格朗日启发式方法,开发了宝钢生产订单调度模拟系统。对多达100个订单的问题的计算结果表明,所提出的拉格朗日松弛方法是稳定的,并且可以在合理的时间内找到良好的解决方案。 (c)2006 Elsevier B.V.保留所有权利。

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