【作者】 邱磊；

【导师】 龚祝平；

【作者基本信息】 华南理工大学 ， 管理科学与工程（专业学位）， 2019， 硕士

【摘要】 生产排产优化问题一直是制造企业生产车间面临的难题之一,传统的生产排产问题仅仅考虑到企业的经济效益方面,但随着经济的可持续发展和环境污染问题日益严重,传统生产调度方法所考虑的因素不足以满足社会效益的要求。因此,从绿色发展的角度出发考虑节能减排的能耗优化调度问题,实现降耗生产调度是现今许多制造企业当务之急,也是学术界研究的热点之一。本文通过综述相关文献,梳理了国内外研究现状,借鉴标准三元组表达式描述了本文所研究的问题,具体指的是以面向订单生产、作业具有可拆分性的同类并行机制造车间为研究对象,研究在给定n个可拆分加工的作业和m台同类不同速加工机器的情况下,考虑拖期成本和能耗两方面权衡优化,从而根据实际的场景需求给出调度方案。在整个调度过程中,每个作业有各自的交货期和单位拖期惩罚成本,不同机器有不同的生产效率和不同的单位生产能耗,调度的目标是给出调度方案使得企业拖期成本尽可能低、生产能耗尽可能少。根据对研究问题的描述,建立了考虑拖期成本与能耗的同类并行机排产调度模型,其中目标函数包括最小化拖期成本和最小化能耗。接着为了求解模型,在标准遗传算法基础上引入了多种群、自适应性和局部搜索策略,同时提出了个体差异度以控制交叉方式的选择,设计了改进的遗传算法。之后通过算例数据进行数值实验,验证模型和算法的有效性。最终结果表明改进算法性能良好,对于不同场景和不同规模的问题,其在计算结果、计算速度上都表现出了较为稳定的性质,并且计算效果普遍优于标准遗传算法,说明本文的改进算法具有良好的稳健性和收敛性。简而言之,本文运用系统工程的思想、最优化理论和方法,建立了拖期成本最小化和能耗最小化的数学模型,并设计了改进的遗传算法进行求解。研究结果表明本文模型符合企业实际生产情况,所设计的算法具有良好的稳健性和收敛性,并能够处理不同场景、不同规模的该类问题,使得文章具有一定的现实意义和创新性。更多还原

【Abstract】 Production scheduling problem has always been one of the difficulties faced by production workshops of manufacturing enterprises.The traditional production scheduling problem only takes into account the economic benefits of enterprises,but with the sustainable development of economy and increasingly serious environmental pollution problems,the factors considered by traditional production scheduling are not enough to meet the requirements of social benefits.Therefore,considering the issue of green scheduling for energy conservation and emission reduction,realizing low-carbon production scheduling is an urgent task for many manufacturing enterprises and one of the hot spots in academic research.This paper reviews the relevant literature,combing the research status at home and abroad.By using the standard expression of Triples for reference,the research problem in this paper is described,which refers to taking manufacturing plant with proces-oriented,proces-separable and uniform parallel machines,as a research object.Under the condition of n separable process and m uniform parallel machines,considering optimization of both energy consumption and tardiness costs,thus according to the actual demands,scheduling scheme is given.In the whole scheduling process,each job has its own delivery time and tardiness cost per unit.Different machines have different production efficiency and different energy consumption per unit production.The goal of scheduling is to provide a scheduling scheme to make the enterprise’s tardiness costs as low as possible,as well as production energy consumption.According to the description of the research problem,this paper establishes a model considering tardiness costs and energy consumption,with uniform-parallel-machine situation.In which the objective function includes minimizing energy consumption and minimizing tardiness costs.Then,in proces to solve the model,a multi-population,adaptive and local search strategy is introduced in the standard Genetic Algorithm.At the same time,Individual Difference Degree is proposed to control the way of crossover,so that an improved Genetic Algorithm is designed.After that,numerical experiments are carried out with the example data to verify the effectiveness of the model and the algorithm.The final results show that the improved algorithm has a good performance.For the problems of different scenes and different scales,it shows a relatively stable property in terms of calculation results and calculation speed,and the calculation effect is generally better than the standard Genetic Algorithm,indicating that the improved algorithm in this paper has good robustness and convergence.To be brief,the theory of system engineering,optimization theory and methods are applied to establish the mathematical model of tardiness costs minimization and energy consumption minimization,and an improved Genetic Algorithm is designed to solve this model.The research results show that the model in this paper conforms to the actual production situation of the enterprise,and the algorithm designed has good robustness and convergence,and can deal with such problems of different scenes and different scales,which makes the paper have a certain practical significance and innovation.更多还原