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模糊决策与模糊调度问题的研究及应用
耿兆强
学位类型工学博士
导师邹益仁
2002-03-01
学位授予单位中国科学院研究生院
学位授予地点中国科学院自动化研究所
学位专业控制理论与控制工程
关键词模糊决策 模糊单机调度 模糊流水车间调度 模糊作业车间调度 遗传算法 非线性规划 进化算法 智能决策支持系统 Fuzzy Decision Fuzzy Single Machine Scheduling Fuzzy Flow Shop Scheduling Fuzzy Job Shop Scheduling Genetic Algorithm Non-linear
摘要模糊性是人类思维和客观事物普遍存在的属性之一,而模糊集合论则是处理 模糊现象的有效工具。模糊决策正是模糊集合论与决策理论相结合的产物。在生 产调度问题中,由于各种随机因素的影响,把加工时间和交货期按模糊数处理更 加符合生产的实际情况,这类调度问题称为模糊调度问题。本文对模糊决策和模 糊调度问题进行了研究。 论文的主要内容和创新之处如下: 1.在对单人多目标决策问题分析的基础上,利用模糊集理论中相对优属度 的定义,引入群体广义海明权距离,提出了解决群体多目标决策问题的方法。并 通过一个具体实例说明了方法的具体应用。 2.在研究单机调度问题的基础上,给出了模糊调度问题的概念。介绍了两 种常用的模糊数三角模糊数和梯形模糊数。基于对模糊加工时间和模糊交货期的 不同考虑建立了三种单机调度模型,采用遗传算法搜索最优排序。仿真实例通过 与启发式算法的比较验证了算法的有效性。 3.研究了模糊多机调度问题,包括模糊流水车间和模糊作业车间调度问题。 给出了三种模糊流水车间调度模型和两种模糊作业车间调度模型。针对作业车间 调度问题的特点,提出了一种新的遗传算法方法,并在遗传算法编码解码、初始 种群产生、交叉变异算子设计等方面做了研究,所提出的方法能自动满足工序约 束。仿真例子验证了算法的有效性和正确性。 4.采用改进的遗传算法和进化规划两种进化算法求解非线形规划问题,并 对编码方法、交叉变异算子设计、约束处理等方面作了讨论。数值仿真结果证明 了算法的有效性。还对进化算法的三种典型方法遗传算法、进化策略和进化规划 进行了比较,简单讨论了遗传算法的数学基础。 5.采用决策支持系统和专家系统并重的结构,研究丌发了基于专家系统工 具的销售管理智能决策支持系统。本系统着重于实现合同的技术可行性分析、最 优交货期确定和合理报价三方面的决策支持。
其他摘要Fuzzy property is one of the most popular properties of mankind thinking and objective things. Fuzzy set theory is an effective tool to deal with fuzzy phenomena. Fuzzy decision is just the result of combination of fuzzy set theory and decision theory. When solving scheduling problems, owing to some random factors, it is more appropriate to consider processing time and due date as fuzzy numbers. This kind of scheduling problems is called fuzzy scheduling ones. This paper studies fuzzy decision and fuzzy scheduling problems, Main works and innovations of this dissertation are as follows. 1. The broad sense Hamming weight distance method for individual multi-objective decision-making is generalized to group one. The definition of relative optimal membership degree used in engineering fuzzy set theory is adopted. The concept of group broad sense Hamming weight distance is introduced. The method of solving multi-objective group decision-making problem is proposed, and an example is presented to illustrate the validity and universality of the given method. 2. The fuzzy scheduling problem is introduced under the basis of single machine problem. Two common kinds of fuzzy number, which are triangular and trapezoid, are introduced. We formulate three kinds of scheduling model according to fuzzy processing time and fuzzy due date. Genetic algorithm is adopted to find the optimal sequencing. Compared with heuristic algorithm, simulation experiment shows the validity of given method. 3. Fuzzy multi-machine scheduling problems, including fuzzy flow shop scheduling problem and fuzzy job shop scheduling problem, are studied. Three kinds of fuzzy flow shop scheduling model and two kinds of fuzzy job shop scheduling model are presented. According to the characteristics of job shop scheduling problem, a new kind of genetic algorithm is given. Researches are made in aspects such as coding, decoding, producing initial population, crossover and mutation, etc. The given method can meet the sequence constraint automatically. In order to show the validity of the algorithm, numerical simulation examples are given. 4. We studies non-linear programming: problem by using improved genetic algorithm and evolutionary programming. Discussions are made in aspects such as coding, crossover and mutation, constraint processing etc. Experimental results show the effectiveness of our proposed algorithm. In addition, we compare the three kinds of typical evolution algorithm that are gene, tic algorithm, evolution strategy and evolutionary programming. We also discuss the mathematical basis of genetic algorithm simply. 5. The expert system based sale management intelligent decision support system (SMIDSS) is researched and developed. The decision support system and expert system are treated equally in the SMII)SS. The SMIDSS can implement the contract's technique feasibility analysis, the optimum due date de
馆藏号XWLW663
其他标识符663
语种中文
文献类型学位论文
条目标识符http://ir.ia.ac.cn/handle/173211/5725
专题毕业生_博士学位论文
推荐引用方式
GB/T 7714
耿兆强. 模糊决策与模糊调度问题的研究及应用[D]. 中国科学院自动化研究所. 中国科学院研究生院,2002.
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