标题: 模糊逻辑于集体生产规之应用
Application of Fuzzy Logic in Aggregate Production Planning
作者: 伍汉庆
H. C. Wu
许锡美
H. M. Hsu
工业工程与管理学系
关键字: 遗传基因演算法;模糊逻辑控制;隶属函数;集体生产规划;Genetic Algorithm; Fuzzy Logic Control; Membership functions; Aggregate Production Planning
公开日期: 1994
摘要: 集体生产规划(aggregation production planning; APP)是在给定有限的
规划幅度内,将工厂的人力及设备资源作最有效利用,以满足预测之顾客
需求。在有限资源共享之前提下,集体生产规划须决定每一期的生产和雇
用的最佳水准。虽然,目前已有不少数学模式和启发式的技巧使用于各种
特定的集体生产规划策略中。但是,这些模式或方法必须依赖精确的参数
估计与函数关系。实际上,决策者常无法精确的估计这些参数估计而给予
确定的函数关系,因此规划结果无法反应产业实际状况,致使管理者认为
这些模式或方法无法代表实际上复杂的运作状况,而对这些数学模式失去
信心。因模糊逻辑不需精确的参数估计与函数关系,因此,本研究拟利用
模糊逻辑于集体生产规划,并运用基因遗传演算法(genetic algorithm;
GA)来调整修正模糊逻辑控制(Fuzzy Logical Control;FLC)中的隶属函数
,并提出修正式的模糊逻辑控制(FLC)模式,以反应生产规划人员在实际
从事规划时所采用的决策过程,进而改善传统集体生产规划技术的缺点,
以发展一套较能为管理者接受的且具弹性和实用性的集体生产规划(APP)
模式。
This study presents a method for combining genetic and fuzzy
algorithms to learn optimal membership functions for aggregate
production planning problems. Generally, the successful
application of fuzzy logic controllers depends on a number of
parameters, such as membership functions, that are usually
subjective creations. It is shown in this study that suitable
membership functions may be designed with the aid of genetic
algorithms. In order to simplify the computation of the fuzzy
logic control, we adopt the trapezoidal fuzzy number as the
shape of membership functions. It is shown that the genetic
algorithm enable us to generate an optimal set of parameters
for these trapezoidal membership functions. The approach
presented here is illustrated by using Holt's HMMS paint
factory data. Comparison of results with Rinks and Turksen
shows that the proposed approach can be used to produce a
favourable result.
URI: http://140.113.39.130/cdrfb3/record/nctu/#NT830030027
http://hdl.handle.net/11536/58791
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