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Computing Minimal Forecast Horizons:An Integer Programming Approach

机译:计算最小预测范围:整数规划方法

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In this paper, we use integer programming (IP) to compute minimal forecast horizons for the classical dynamic lot-sizing problem (DLS). As a solution approach for computing forecast horizons, integer programming has been largely ignored by the research community. It is our belief that the modelling and structural advantages of the IP approach coupled with the recent significant developments in computational integer programming make for a strong case for its use in practice. We formulate some well-known sufficient conditions, and necessary and sufficient conditions (characterizations) for forecast horizons as feasibility/optimality questions in 0–1 mixed integer programs. An extensive computational study establishes the effectiveness of the proposed approach.
机译:在本文中,我们使用整数规划(IP)来计算经典动态批量确定问题(DLS)的最小预测范围。作为计算预测范围的一种解决方法,整数编程已被研究界广泛忽略。我们相信,IP方法的建模和结构优势以及计算整数编程的最新发展为在实践中使用它提供了强有力的证明。我们制定了一些众所周知的充分条件,以及预测范围的必要条件和充分条件(特征),作为0-1混合整数程序中的可行性/最优性问题。广泛的计算研究确定了所提出方法的有效性。

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