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Fuzzy bilevel programming with multiple non-cooperative followers: model, algorithm and application

机译:具有多个非合作跟随者的模糊双层规划:模型,算法和应用

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In centralized decision problems, it is not complicated for decision-makers to make modelling technique selections under uncertainty. When a decentralized decision problem is considered, however, choosing appropriate models is no longer easy due to the difficulty in estimating the other decision-makers' inconclusive decision criteria. These decision criteria may vary with different decision-makers because of their special risk tolerances and management requirements. Considering the general differences among the decision-makers in decentralized systems, we propose a general framework of fuzzy bilevel programming including hybrid models ( integrated with different modelling methods in different levels). Specially, we discuss two of these models which may have wide applications in many fields. Furthermore, we apply the proposed two models to formulate a pricing decision problem in a decentralized supply chain with fuzzy coefficients. In order to solve these models, a hybrid intelligent algorithm integrating fuzzy simulation, neural network and particle swarm optimization based on penalty function approach is designed. Some suggestions on the applications of these models are also presented.
机译:在集中决策问题中,决策者在不确定性下进行建模技术选择并不复杂。但是,在考虑分散决策问题时,由于难以估计其他决策者的不确定性决策标准,因此选择合适的模型不再容易。这些决策标准可能因不同的决策者而异,因为他们具有特殊的风险承受能力和管理要求。考虑到分散系统中决策者之间的一般差异,我们提出了一个模糊双层规划的通用框架,其中包括混合模型(与不同层次的不同建模方法集成)。特别地,我们讨论其中的两个模型,它们可能在许多领域具有广泛的应用。此外,我们使用提出的两个模型来制定具有模糊系数的分散式供应链中的定价决策问题。为了解决这些模型,设计了一种基于罚函数法的模糊仿真,神经网络和粒子群优化相结合的混合智能算法。还提出了有关这些模型的应用的一些建议。

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