多模态多目标混合流水车间调度进化优化算法研究

Multi-objective hybrid flow shop scheduling problems with multi-modal are commonly seen in industry production. These problems have not only more than one objective with conflicting, but one with multi-modal properties, which add more difficulties in achieving all Pareto optimal solutions, and become a hot area of research in the production scheduling fields, however, not yet been well studied in theories and methods. In view of this, this project is presented to study evolutionary optimization ralgorithm esearch on multi-modal multi-objective hybrid flow shop scheduling. First, a mathematical model of multi-modal multi-objective hybrid flow shop scheduling problem is constructed. Second, a classification method of decision variables based multi-modal-character-perceptive is proposed by using the machine learning and probability distribution theory. In addition, the optimization mechanism of many evolutionary algorithms is studied to design decision-information-guided evolutionary optimization method of the scheduling strategies. Last, we apply the above theories and methods into the iron scheduling problems in steel-making casting systems. This research project is a novel and interdisciplinary research orientation. The research achievements will enhance and improve the theory of the hybrid flow shop scheduling problem with multi-modal multi-objective, promote the application and popularity of evolutionary optimization scheduling algorithms, bring enormous economic benefit and social benefit for the industries, and have great theory significance and utility value.

多模态多目标混合流水车间调度问题非常普遍，该问题不但有多个相互冲突的目标函数，而且其目标函数还具有多模态特性，从而大大增加了问题求解的难度，成为近年来生产调度领域的研究热点之一。但是，到目前为止，尚缺乏有效解决该问题的理论与方法。鉴于此，本项目研究多模态多目标混合流水车间调度进化优化算法。通过研究，拟建立多模态多目标混合流水车间调度问题的数学模型，设计基于多模态特性感知的调度决策变量分类策略，提出决策信息引导的调度方案进化生成方法，并应用于铁水生产调度问题中。本项目是多学科交叉的新颖研究方向，产生的研究成果能够丰富多模态多目标混合流水车间调度理论，扩大优化调度方法的应用范围，并为企业带来非常可观的经济和社会效益，具有重要的理论意义和实用价值。

多模态多目标混合流水车间调度问题非常普遍，该问题不但具有多个相互冲突的目标函数，而且其目标函数还具有多模态特性，从而大大增加了问题求解的难度，成为近年来生产调度领域的研究热点之一。但是，到目前为止，尚缺乏有效解决该问题的理论与方法。鉴于此，本项目研究多模态多目标混合流水车间调度进化优化算法。通过研究，拟建立多模态多目标混合流水车间调度问题的数学模型，设计基于多模态特性感知的调度决策变量分类策略，提出决策信息引导的调度方案进化生成方法，并应用于铁水生产调度问题中。本项目是多学科交叉的新颖研究方向，产生的研究成果能够丰富多模态多目标混合流水车间调度理论，扩大进化优化调度方法的应用范围，并为企业带来非常可观的经济和社会效益，具有重要的理论意义和实用价值，在本项目的支持下，共完成37篇学术成果，培养硕士研究生6名，申请发明专利1项，软件著作权2项。