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A combined facility location and network design model with multi-type of capacitated links and backup facility and non-deterministic demand by fuzzy logic

机译：设施类型与网络设计相结合的模型，其中包含多种类型的有能力的链路和备份设施，并且通过模糊逻辑确定需求

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摘要

Recently so many researches are concerned with the combined facility location and network design models for facility location and coverage problems. In this models we want to find the optimum location of facility by constructing an underlying network. We can use this for distribution network, transportation networks, health centers and emergency allocations, etc. At this study a mathematical programming model is introduced that facilities are opened on the nodes and it is assumed for connecting demand nodes and facilities there are different links with different quality that just one of them should be selected. Also if a facility in a node can't satisfy demand the demand is sent to a facility in other node and satisfied by this facility called backup facility. Also decision process is affected by uncertainty and concept of information inherently is mixed with uncertainty. Fuzzy logic can introduce mathematical models for hazy concepts and variables and systems and also showing a way for argument, control and making decision in uncertainty condition. In complex systems with high uncertainty fuzzy logic is best way for the modeling. At this study demands are considered in uncertain form and are introduced in the form of fuzzy numbers. The problem is modeled for different size and the computational results are compared.
机译：最近，许多研究关注设施定位和覆盖问题的组合设施定位和网络设计模型。在此模型中，我们希望通过构建基础网络来找到设施的最佳位置。我们可以将其用于配电网络，运输网络，卫生中心和紧急情况分配等。在本研究中，引入了一种数学编程模型，即在节点上开放设施，并假定用于连接需求节点和设施之间存在不同的联系。仅选择其中一种的不同质量。同样，如果节点中的设施不能满足需求，则将需求发送到其他节点中的设施，并通过称为备份设施的设施来满足需求。决策过程也受到不确定性的影响，信息的概念固有地与不确定性混合在一起。模糊逻辑可以为模糊概念，变量和系统引入数学模型，并为不确定性条件下的论证，控制和决策提供一种方法。在具有高度不确定性的复杂系统中，模糊逻辑是进行建模的最佳方法。在本研究中，需求以不确定形式考虑，并以模糊数形式引入。针对不同的大小对问题进行建模，并对计算结果进行比较。

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