导　　师： 杨海东

学科专业： 0802

授予学位： 硕士

作　　者： ;

机构地区： 广东工业大学

摘　　要： 随着能源需求的急剧增加和全球能源价格不断攀升,能源逐渐成为制约制造型企业生存和发展的关键因素。通过降低能耗来减少生产成本对于轮胎、水泥和钢铁等高能耗制造行业的发展具有重要意义。生产调度作为企业组织执行生产进度计划的主要环节,是企业组织生产、优化资源配置、提高生产效率、降低生产成本的重要技术手段,而目前国内以节能降耗为目标的车间生产调度研究才刚起步。本文以轮胎硫化车间为背景,抽象出一类非同等并行机调度问题,开展以考虑拖期成本和能耗成本为目标的非同等并行机调度问题的研究,建立了非同等并行机能耗成本优化调度模型,并对模型进行优化；在此基础上,分别运用启发式规则和基于启发式规则遗传算法对该能耗模型进行求解；最后,将该模型应用到广州丰力橡胶轮胎公司硫化车间的实际生产调度中,取得了良好的效果。 本论文在综述能耗优化调度低碳制造及节能降耗调度研究意义与发展现状的基础上,对以下内容进行了深入研究： 1.对以能耗优化目标的非同等并行机调度问题及求解方法进行分析,构建了以能耗成本和拖期成本为目标的非同等并行机调度问题的数学模型。模型对轮胎企业能源分布情况、生产工艺能耗影响因素、硫化能耗输入-输出等要素进行了描述,为后文的研究提供理论依据。 2.针对以能耗优化为目标的非同等并行机调度问题,采用基于启发式规则算法进行求解；针对优化模型中的拖期成本目标,采用三种基于优先启发式规则的算法进行求解；针对能耗优化目标,提出基于机器能耗规则的启发式算法,针对能耗成本和拖期成本目标,提出基于组合启发式规则的算法对模型进行求解。为验证算法有效性,设计了仿真算例对该模型进行仿真,仿真的结果验证了本模型的合理性和有效性。 3.针对硫化车间能耗优化调度问题,提出基于启发式规则的遗传算法进行求解。为检验不同启发式规则进行初始化对遗传算法性能的影响,采用了4种基于规则遗传算法与普通遗传算法进行对比,并依次设计了大量仿真实验。实验结果证明了利用规则寻找初始种群的混合遗传算法相较普通遗传算法的优越性。此外,还将建立的能耗优化模型应用于硫化车间生产调度过程中,实验结果表明,本文建立的能耗优化调度模型能够有效降低制造过程能耗成本。 "Since demand for energy is sharply increased and the price of energy resources rise intensely, energy gradually becomes a key factor for manufacturing enterprises. To reduce the cost of production for high energy consumption industry, such as cement and steel by reducing energy consumption is of great significance, production scheduling, as the main part of enterprise schedule organization, becomes an important technical means for enterprise production organization, resource allocation optimization, production efficiency promotion. Currently, domestic study for production scheduling aiming at energy consumption reduction has just started. Based on the tire vulcanization workshop, a class of non identical parallel machine scheduling problem is abstracted, in this paper. By taking the tardiness costs and energy costs into consideration, a non identical energy consumption cost optimization of parallel machine scheduling model is established and optimized. On this basis, heuristic rules and heuristic rules based genetic algorithm for solving the energy consumption model are used respectively. Finally, the model is applied to the practical production scheduling of vulcanizing workshop in Fengli rubber tire company in Guangzhou, and good results are achieved. In this paper, based on energy optimization of scheduling research significance and development of low carbon manufacturing and energy saving scheduling, the following contents are studied: INon identical parallel machine scheduling problem aiming at energy optimization is analyzed. Anon-identical parallel machine scheduling problem mathematical model based on the energy consumption cost and tardiness cost objectives is constructed. The model depicts the tire enterprise energy distribution, energy consumption factors in manufacturing, power consumption in vulcanization and other factors, and provide a theoretical basis for the afterwards research. 2An algorithm based on heuristic rules is used to solve the non identical parallel machine scheduling problem aiming at energy optimization, where three kinds of algorithms based on the priority heuristic rules are used. Aiming at energy consumption cost as the goal of the optimization model, A heuristic algor, proposed based on the rule of the machine energy consumption to optimize the ml In order to validate the algorithm, a simulation example is designed to simulate model, and the simulation results verify the rationality and validity of the present model. 3For vulcanizing workshop scheduling problem of energy optimization, a genetic algorithm based on heuristic rules in order to test the influence of different heuristic rules using4types of genetic algorithm are initialized to the performance of genetic algorithm. The result is compared with the ordinary genetic algorithm based on sequence, and the design of a large number of simulation experiments. Experimental results show the superiority of the use of rules for hybrid genetic algorithm initial population compared with the ordinary genetic algorithm. In addition, the energy optimization model is applied to the vulcanization workshop production scheduling process, the experimental results show that, the energy optimal scheduling model can effectively reduce the energy cost of manufacturing process.

关 键 词： 生产调度 能耗成本 拖期成本 启发式算法 遗传算法

分 类 号： [TQ336.1]

领　　域： [化学工程]