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首页> 外文期刊>International Journal of Manufacturing Technology and Management >Optimisation of distribution networks using Genetic Algorithms. Part 1 - problem modelling and automatic generation of solutions
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Optimisation of distribution networks using Genetic Algorithms. Part 1 - problem modelling and automatic generation of solutions

机译：使用遗传算法优化配电网络。第1部分-问题建模和解决方案的自动生成

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This paper presents a generalised methodology developed for the optimisation of the distribution networks based on Genetic Algorithms (GA). Specifically, it focuses on capacitated Location-Allocation problems. The approach is general, permitting, at this stage, the use of any combination of transportation and warehousing costs for a deterministic demand. Moreover, the methodology has been designed to have the flexibility to be adapted, in the future, for other realistic conditions and constraints: stochastic conditions, multi-echelon Supply Chain, direct and reverse logistics, single or multi-commodities, seasonal production, etc. Due to the complexity and extent of the problem, the paper was split into two parts. The first part deals with modelling of the problem and the automatic generation of the initial population of chromosomes - a set of solutions to the problem. The second part of the paper details the full GA and the genetic operators. An example of applying the algorithm for 25 Production Facilities (PFs), 10 warehouses and 25 retailers (520 variables interrelated with complex constraints) is presented, demonstrating the robustness of the algorithm and its capacity to tackle problems of practical size.
机译：本文介绍了一种基于遗传算法（GA）开发的用于优化配电网络的通用方法。具体来说，它着重于有限的位置分配问题。这种方法是通用的，在此阶段允许将运输和仓储成本的任何组合用于确定的需求。此外，该方法的设计具有灵活性，可在将来适应其他实际条件和约束：随机条件，多级供应链，直接和反向物流，单一或多种商品，季节性生产等由于问题的复杂性和程度，本文分为两部分。第一部分处理问题的建模和自动生成初始染色体种群-解决问题的方法。本文的第二部分详细介绍了完整的遗传算法和遗传算子。给出了将该算法应用于25个生产设施（PF），10个仓库和25个零售商（520个变量与复杂约束相关联）的示例，展示了该算法的鲁棒性及其解决实际规模问题的能力。

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