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Using Metaheuristic and Fuzzy System for the Optimization of Material Pull in a Push-Pull Flow Logistics Network

机译：运用元启发式和模糊系统优化推拉流物流网络中的物料牵引

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摘要

Alternative material flow strategies in logistics networks have crucial influences on the overall performance of the networks. Material flows can follow push, pull, or hybrid systems. To get the advantages of both push and pull flows in networks, the decoupling-point strategy is used as coordination mean. At this point material pull has to get optimized concerning customer orders against pushed replenishment-rates. To compensate the ambiguity and uncertainty of both dynamic flows, fuzzy set theory can practically be applied. This paper has conceptual and mathematical parts to explain the performance of the push-pull flow strategy in a supply network and to give a novel solution for optimizing the pull side employing Conwip system. Alternative numbers of pallets and their lot-sizes circulating in the assembly system are getting optimized in accordance with a multi-objective problem; employing a hybrid approach out of meta-heuristics (genetic algorithm and simulated annealing) and fuzzy system. Two main fuzzy sets as triangular and trapezoidal are applied in this technique for estimating ill-defined waiting times. The configured technique leads to smoother flows between push and pull sides in complex networks. A discrete-event simulation model is developed to analyze this thesis in an exemplary logistics network with dynamics.
机译：物流网络中的替代物料流策略对网络的整体性能具有至关重要的影响。物料流可以遵循推，拉或混合系统。为了获得网络中推流和拉流的优势，将解耦点策略用作协调手段。在这一点上，必须针对推销的补货率针对客户订单优化物料拉动。为了补偿两种动态流的模糊性和不确定性，可以实际应用模糊集理论。本文具有概念和数学部分，以解释供应网络中的推挽式流动策略的性能，并提供一种使用Conwip系统优化拉动侧的新颖解决方案。根据多目标问题，正在组装系统中循环使用的托盘的备用数量及其批次大小正在得到优化。在元启发法（遗传算法和模拟退火）和模糊系统中采用混合方法。在此技术中，使用了两个主要的模糊集（三角形和梯形）来估计未定义的等待时间。配置的技术可在复杂网络中的推拉侧之间产生更平滑的流动。建立了离散事件仿真模型，以在具有动力学的示例性物流网络中分析本文。

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  • 来源
    《Mathematical Problems in Engineering》 |2013年第1期|359074.1-359074.19|共19页
  • 作者

    Afshin Mehrsai; Hamid-Reza Karimi; Klaus-Dieter Thoben; Bernd Scholz-Reiter;

  • 作者单位

    International Graduate School for Dynamics in Logistics, University of Bremen, c/o BIBA, Hochschulring 20,28359 Bremen, Germany;

    Department of Engineering, Faculty of Engineering and Science, University of Agder, 4879 Grimstad, Norway;

    International Graduate School for Dynamics in Logistics, University of Bremen, c/o BIBA, Hochschulring 20,28359 Bremen, Germany;

    International Graduate School for Dynamics in Logistics, University of Bremen, c/o BIBA, Hochschulring 20,28359 Bremen, Germany;

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