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Interactive fuzzy programming for multi-level programming problems: a review

机译:用于多层编程问题的交互式模糊规划:综述

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Decision-making problems in decentralised organisations are often modelled as Stackelberg games, and they are formulated as two-level mathematical programming problems with two decision-makers. If they do not have any motivation to cooperate mutually and behave rationally, outcomes of the problems can be explained by Stackelberg equilibrium which is not always Pareto optimal. From computational aspects, it is known that solving two-level programming problems is NP-hard even if the objective functions and the constraint functions are linear. In contrast, if the decision-makers can select strategies cooperatively, the most important aspect is to derive a Pareto optimal solution favourable to the decision-makers. As a method of this line of approach interactive fuzzy programming has been developed, taking into account fuzziness of human judgements. In this paper, after reviewing the development of solution methods for two- and multi-level programming problems, we focus on cooperative decision-making in decentralised organisations and give interactive fuzzy programming for two-level linear programming problems, which provides satisfactory solutions in accordance with the preference of the decision-makers. Moreover, we present extensions of interactive fuzzy programming for two-level linear programming problems under multi-objective environments and under uncertainty.
机译:分散组织中的决策问题通常被建模为Stackelberg游戏,它们被表述为具有两个决策者的两级数学编程问题。如果他们没有相互合作和理性行为的动力,那么问题的结果可以用斯塔克伯格均衡来解释,而斯塔克伯格均衡并不总是帕累托最优的。从计算方面来看,即使目标函数和约束函数是线性的,解决两级程序设计问题也是NP难的。相反,如果决策者可以合作选择策略,则最重要的方面是得出对决策者有利的帕累托最优解。作为这种方法的一种方法,已经开发了交互式模糊规划,同时考虑了人类判断的模糊性。本文在回顾了两层和多层规划问题的求解方法的发展之后,着重研究了分散组织的合作决策,并给出了针对两层线性规划问题的交互式模糊规划,从而提供了令人满意的解决方案。与决策者的偏好。此外,我们提出了在多目标环境和不确定性下针对两级线性规划问题的交互式模糊规划的扩展。

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