动态复杂环境下拆卸线平衡问题群集拟生态模型与方法研究

Disassembly is an important process for realizing the integrity and closed-loop of the life cycle of products. Disassembly line balancing problem (DLBP) as a new proposed problem and still unsolved hard problem, the study of DLBP is with important theoretical and practical significances. Considering complexity of DLBP in dynamic complex environment, the model of DLBP with stochastic, mixed-model and other complex characters will be constructed first, and then the study focus on two aspects of mechanism simulation and rules follow based on swarm simulation ecology model and methods. Learn from the ecological behavior of social insects, meta-heuristic algorithms will be constructed and be applied to DLBP. Furthermore, through integrate with the characters of DLBP and hybrid algorithms mechanism to improve the performance, in order to overcome the limitation in velocity and quality for solving the large problems. On the other hand, i.e. rules follow of social insects, the simple rules will be constructed through follow the behavior of social insects, such as ants, bees. By using the advantages of its flexibility, robustness and self-organization, the self-balancing methods for disassembly line will be established to realize the self-organization optimization and improve the dynamic responsibility of disassembly line. Through the research of the project, theoretical innovation in related with DLBP will be achieved, and the new methods of actual operation for disassembly line will be obtained. Considering suitable for the demands of the recycle of the resources, the project has a very broad application prospects.

拆卸是构筑产品生命周期完整性与封闭性的必要环节，拆卸线平衡问题是一个新近产生、尚未解决的科学难题，研究具有重要的理论与实际意义。项目针对动态复杂环境下拆卸线平衡问题的复杂性，构建协同考虑随机、混流等复杂特征的拆卸线平衡问题数学模型，采用基于群集拟生态模型的新方法在机理模拟与规则仿效两方面展开探索和研究。在机理模拟上，借鉴蚁群、蜂群等社会性昆虫的生态行为，构造群集智能优化算法应用于拆卸线平衡问题，并结合问题特征及算法混合机制等改进算法，以求在求解速度和求解质量方面突破问题规模的制约；在规则仿效上，通过模拟蚁群、蜂群等有关行为来构造相关简单规则，利用其灵活性、稳健性、自组织等优点，建立拆卸线自平衡方法，以实现拆卸线作业的自组织优化，并提高拆卸线的动态响应能力。本项目既能获得拆卸线平衡方面的理论创新，也能给拆卸线实际运作提供有效方法，适应当前资源回收发展的迫切需要，因而具有非常广阔的应用前景。

拆卸作为构筑产品生命周期完整性与封闭性的必要环节，拆卸线平衡问题是一个新近产生、尚未很好解决的科学难题，研究具有重要的理论与实际意义。在基金青年项目资助下，开展了动态复杂环境下拆卸线平衡问题的相关研究。通过研究，项目取得了如下主要研究成果：项目针对动态复杂环境下拆卸线平衡问题的复杂性，构建了有关特征的拆卸线平衡问题数学模型。针对拆卸线平衡问题，从群集拟生态模型中发展了群集智能优化算法，进一步提出了改进的蚁群算法、粒子群算法、蜂群算法、细菌觅食优化算法等群集智能优化方法，求解动态复杂环境下的拆卸线平衡问题。并结合问题特征，开展动态复杂环境下的拆卸线平衡问题的群集智能优化算法性能卓越化的研究，在求解速度和求解质量方面能有效突破问题规模的制约。应用混合算法进一步提升算法性能，将混合遗传算法的改进粒子群算法与小生境技术进行混合，有效解决了多目标拆卸线平衡问题。针对拆卸线设备生产布局，提出了分别针对单行布局问题和双行布局问题的求解方案。分析群集拟生态模型，仿效社会性昆虫建立相关规则，探索了动态复杂环境下拆卸线自平衡。相关研究成果有助于丰富绿色设计与制造下的拆卸线设计理论，适应当前资源回收发展的迫切需要，为实际的拆卸线设计亦有一定的参考价值。