基于离散入侵性杂草优化和问题结构特性的批量流调度方法研究

项目名称： 基于离散入侵性杂草优化和问题结构特性的批量流调度方法研究

项目编号： No.61503170

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 自动化技术、计算机技术

项目作者： 桑红燕

作者单位： 聊城大学

项目金额： 22万元

中文摘要： 近年来，广泛存在于瓷砖、变压器铁芯和太阳能电池等生产过程的批量流调度问题成为国际上的研究热点之一。智能优化方法成为最主要的求解方法。但现有调度方法较少利用问题特性来提高算法性能，且主要针对单目标的调度问题。多目标批量流调度问题的研究还刚刚起步，缺乏针对动态不确定批量流调度问题的研究。本项目在前期探索的基础上，将深入研究基于离散入侵性杂草优化（DIWO）和问题特性的批量流调度方法，包括研究新颖的DIWO操作算子、协同进化的算法框架、基于学习机制的控制参数设定方法以及算法收敛性、计算复杂性、有限时间性等理论，研究批量流调度问题的邻域结构、邻域连通性和适应度地貌等问题特性，探索DIWO与问题特性的有机结合方法，提出针对单目标、多目标和动态批量流调度问题的高性能优化算法，给出一批具有工程应用价值的批量流调度理论成果, 可望直接服务于我国瓷砖、变压器铁芯和太阳能电池等企业的生产过程。

中文关键词： 入侵性杂草优化算法；批量流；调度；多目标；动态

英文摘要： In recent years, the lot-streaming flow shop scheduling problem, which has important applications in tile, transformer core, solar cell, and many other modern industries, has become a hot area of research. Intelligent optimization algorithms have become the main solution techniques. The existing scheduling methods, however, make little use of the problem-specific properties to improve their performance. And almost all the literature focuses on a single objective. The scheduling method for the multi-objective lot-streaming scheduling problems is still in its infancy. To our best knowledge, there is no literature on the lot-streaming scheduling problems in dynamic environments. Therefore, in this proposal, based on our previous work, we intend to study the lot-streaming scheduling methods based on the discrete invasive weed optimization (DIWO) and the problem-specific characteristics. For the DIWO, we will study the novel operators, co-evolution mechanism, selection of control parameters based on learning mechanism, convergence, computing complexity, and finite time performance. For the problem-specific properties, we will research neighborhood structures, neighborhood connectivity, fitness landscape and etc. we will explore the effective combination of the DIWO and the problem-specific characteristics of the lot-streaming problems. We will propose a series of high-performance algorithms for single objective, multi-objective, and dynamic lot-streaming problems. The research production is expected to be applied in the production process of tile, transformer core, solar cell and many others.

英文关键词： invasive weed optimization algorithm;lot-streaming ;scheduling;multi-objective;dynamic