考虑能耗节约的集装箱码头双小车岸桥与AGV联合配置及调度优化

合理调度集装箱码头的装卸设备以减少生产过程中的能耗, 对实现其低碳绿色化发展具有重要意义. 针对集装箱码头向自动化发展过程中的双小车岸桥与AGV (Automated guided vehicle)联合配置及调度问题, 考虑AGV续航时间、双小车岸桥中转平台容量和堆场缓冲支架容量约束, 以岸桥的能耗最小为第一阶段模型的优化目标, 以AGV运输过程的能耗最小为第二阶段目标建立两阶段优化模型; 设计枚举法求解第一阶段模型, 改进遗传算法求解第二阶段优化模型. 以洋山四期自动化集装箱码头为例进行实验分析, 针对不同船舶在港总装卸时间和AGV配置原则进行实验, 验证了模型和算法的有效性, 结果表明以最小化能耗为目标的双小车岸桥与AGV联合调度可在岸桥主小车不延误的前提下, 显著减少AGV的配置数量.     

考虑双小车岸桥中转平台的AGV调度问题研究

针对双小车岸桥下的AGV 调度问题进行了研究,考虑了双小车岸桥上的中转平台及其容量限制,以岸桥前小车作业延迟时间和岸桥后小车与AGV间的等待时间之和最小为目标函数,建立了带有时间窗约束的AGV调度混合整数规划模型,设计了启发式算法求解后小车时间窗,并采用遗传算法对模型进行求解,获得了基于岸桥后小车作业时间窗的AGV调度优化方案。算例结果表明：双小车岸桥的应用能够有效的降低设备间的等待时间,从而缩短港口整体装卸时间。     

具有$1+N$节点的多重边赋权驱动响应 复杂网络复域函数投影同步

针对复数域上具有$1+N$节点的多重边赋权驱动响应复杂网络的函数投影同步问题,提出一种简单有效的控制方法.首先,构建$1+N$多重边赋权驱动响应复杂网络模型,网络节点为复混沌系统;然后,定义同步尺度函数为复变量,设计混合反馈控制器,并构造相应的正定函数,利用李雅普诺夫稳定性定理和线性矩阵不等式变换给出同步的充分条件.仿真结果验证了所提出方法的有效性,同时揭示了网络节点重边数对同步速度的影响.     

考虑电池包数量的自动化集装箱码头多AGV调度优化

针对自动化集装箱码头自动引导小车（automated guided vehicle,AGV）的实际换电特性,为了降低AGV的总任务完成时间和换电总时间,合理规划换电站内的电池包数量,建立了双层规划模型。首先考虑AGV的电池续航、空重载SOC变化特性和不同剩余电量与速度变化,以降低AGV的总任务完成时间为目标,构建考虑换电的多AGV集装箱任务调度上层模型。在此基础上,为了合理规划换电站内的电池包数量,考虑自动化码头中换电站的实际电池包选取原则和换电流程,对换电站和电池包的选择进行决策,以降低换电总时间为目标,构建换电电池包配置下层模型。最后通过遗传算法分别对小规模和大规模算例进行求解。算例结果表明,此双层规划模型能够有效地减少总任务完成时间和换电总时间,提高了6.46%的AGV利用率,减少了23.1%的换电站电池包数量。     

多意象驱动下的产品造型个性化定制系统研究

构建了一种基于多意象驱动下的产品个性化定制系统,增加用户对个性化定制的体验度,从而实现智能的产品个性化定制设计。通过对当下三种产品个性化定制模式的比较研究和分析,提出了个性化定制系统的构架模型和系统流程。然后通过用户参与模式、感性意象挖掘、关联方法建立多意象驱动机制,并结合感性工学的相关研究方法、BP神经网络以及多目标粒子群算法构建了面向产品意象造型的智能设计模型,实现了多意象驱动下的产品造型个性化定制。最后以人形卡通文具的个性化定制进行了实例验证。结果表明多意象驱动的产品造型个性化定制系统更加丰富了消费者对产品造型意象风格的体验,满足了消费者日益迫切的个性化设计需求,符合智能时代对产品设计开发的需要。     

面向FMS基于改进的混合PSO-GA的多AGV调度算法研究

在柔性制造系统(Flexible Manufacturing System,FMS)中,自动导引小车(Automated Guided Vehicle,AGV)常被用于搬运物料或产品,因此AGV的优化调度成为提高生产效率的关键。AGV的调度除了要考虑AGV的任务分配问题,还需要参考每个操作的花费时间、小车的运行时间等因素。相比于单AGV调度算法,多AGV多任务调度算法需要一个更加复杂的模型来支撑。在考虑AGV的电量状况下,以最小完成时间与调度最少AGV数量作为优化目标,提出了一种改进的混合遗传算法与粒子群算法(PSO-GA),并基于该算法给出了多AGV调度模型,在此基础上进行了仿真实验。结果表明,相较于单一的GA或PSO算法,所提算法在全局寻优收敛与运行时间上有明显的优化效果,而相比于现有的混合PSO-GA算法,其在搜索精度和收敛速度上有进一步提高。     

多搬运任务下考虑碰撞避免的AGV路径规划

为提升自动导引小车在“货到人”仓库中的运行效率,针对AGV-托盘任务分配、单AGV路径规划及多AGV碰撞避免三个子问题的研究,以最小化AGV行驶距离为目标构建数学模型。首先,根据AGV与托盘的双边匹配问题特点设计改进的匈牙利算法求解匹配结果。其次,提出一种二维编码机制的改进遗传算法（improved genetic algorithm,IGA）,采用一种局部搜索算子代替原变异操作,在提高算法搜索性能的基础上使其成功应用于单AGV路径规划问题。然后,利用时空数据设计一种三维网格冲突检测方法,并根据商品SKU数量设定AGV的优先级以降低多AGV执行任务时的碰撞概率。最后,在32 m×22 m的仓库中针对不考虑碰撞与考虑碰撞两种情形进行AGV路径优化分析,给出合理的行驶距离和碰撞次数。IGA与标准遗传算法的对比结果显示,IGA能够在合理的时间内获得更高质量的解,行驶距离减少约1.74%,算法求解时间缩短约37.07%。此外,针对AGV数量灵敏度分析,在不同目标托盘规模下测试不同数量的AGV对行驶距离和碰撞次数的影响,发现14~16台AGV数量是最佳配置,验证了模型的可行性和算法的有效性。     

元路径选择和矩阵分解的跨社交网络链路预测

基于多源社交网络上的用户信息实现跨网络链路预测具有重要的意义,有助于进行用户推荐、行为分析、偏好推荐。传统的链路预测技术仅考虑社交网络上的局部结构特征,有些网络规模庞大、节点稀疏、存在大量孤立点,易导致建模困难、计算效率低等问题。基于此,提出了一种基于元路径选择和矩阵分解的跨社交网络链路预测方法。首先,根据跨社交网络中用户间的社会关系构建一个网络图;然后,利用元路径的节点活跃度和边的活跃度自动提取特征;接下来,利用矩阵分解将目标类型对象相关的元路径信息在低维空间上显示;最后,利用集成分类方法对链接模型进行优化。实验数据表明,提出的链路预测方法具有较高的准确性。     

多AGV和机器集成的多目标柔性作业车间调度研究

为解决智能制造环境中具有多时间和多AGV约束的柔性作业车间调度问题,构建了以最小化最大完工时间、最小化总延期、最小化设备总负荷为目标的机器/AGV双约束多目标调度模型,模型中综合考虑加工时间、工件到达时间、交货期等多时间因素,进行了多AGV和机器集成调度。为求解该模型,设计了新的AGV调度规则和改进的NSGA-算法,算法中提出了基于工序的扩展染色体编码方式和基于AGV分配的贪婪式解码策略,同时设计了不同参数控制的多种群二元锦标赛选择和分段交叉变异策略以及基于Pareto级的去重精英保留策略,以促进个体协同优化搜索。通过实例实验,分析了不同AGV数量任务分配方案下的模型有效性,对4个案例的仿真测试和同类算法比较解也验证了改进NSGA-算法求解该模型的有效性。     

基于图卷积神经网络的在线社区行为预测

在线知识社区中,问题的回答可以看作多个回答者用户(领域专家)之间的协作行为。协作行为在知识社区中通常是大规模地发生,协作行为预测对在线社交中领域专家的推荐有重要意义。基于在线知识社区中回答者用户之间的协作行为,构建以领域专家为节点,以他们之间的协作回答关系为边的协作网络。由于协作行为网络的构建与社交关系网络的构建上结构的相似性,可以将协作行为预测构建为协作网络中的链接预测问题。通过构建基于图卷积神经网络的链接预测模型,对在线知识社区中回答者用户的协作行为进行预测。基于“知乎”数据集的实验验证,与其他经典的预测方法进行比较时,发现提出的方法能够更加有效地预测在线知识社区中回答者用户之间的协作行为。     

A method of constructing an inspiration library driven by user-perceived preference evaluation data for biologically inspired design

Biologically inspired design (BID) is one of the common methods for product design. To solve the problem of inaccurate acquisition of inspirational creatures due to the lack of user perception preference analysis, a data-driven intelligent service model for BID considering user perception needs is proposed based on Kansei engineering. Firstly, by extracting the perceptual features of creatures from the semantic source elements of products through mapping and encodes them, we proposed a data acquisition method based on intuitionistic fuzzy sets considering different customer preference distributions, bridging the gap caused by the asymmetry between designers and users. Secondly, the functional relationship between biometric features and user-perceived attributes is identified and predicted, and a predictive model of biodata considering user preferences is obtained by multiple linear regression analysis. Finally, based on the data clustering and reorganization theory to understand the organization and dynamics of the database, the construction of a BID library was completed, and the design resources in the library were used as analyzed knowledge for designers to plan design activities. Taking the bionic design of a UAV product as an example, a prototype of a computer-aided design service system was developed based on the theory proposed in the article, and the analyzed knowledge was used to improve the efficiency and science of the design, effectively verifying the usefulness of this study for design. To a certain extent, this study addresses the problem of cognitive limitations of designers and cognitive differences between designers and users, promotes the application of bioinspiration in product design, and improves the marketability of design solutions.     

Research on construction and application of gene network model for form design based on consumer’s preference

With developments in science and technology, product innovation is the key to enterprise performance in the competitive market. In consumer demand-oriented modern product design, effectively combining product design with the esthetic perceptions and preferences of consumers is a problem that urgently needs to be addressed. However, the traditional design method is completely dominated by designers without user participation. The purpose of this study was to give designers an impetus for restructuring and upgrading a design. A gene network design model was developed with the advantages of a gene network and neural network. This allowed the target elements of a product design to be obtained using a nonlinear network. Finally, a case study was used to show the detailed procedure of the design model. To reveal the advantages of the proposed model, it was compared with other methods such as a gene-based design method, an emotional design method, and a fuzzy Kano design method. The results showed that the proposed model was more efficient and scientific, and provided consumers with a multidimensional evaluation system to determine the optimal design schemes.     

基于集成化知识的产品概念设计技术研究

从用户知识出发，通过对用户内隐性知识的获取、表征、传递、运用的研究，探讨了“用户意象与设计知识”的映射以及“特征基、特征和风格”三层表达体系；建立了用户内隐性知识的获取、表征与运用模型，设计知识的表达模型，用户知识与设计知识的整合模型；提出了基于集成化知识的产品概念设计理论，以手机设计系统为例进行了验证，支持用户和设计师在同一个平台上协同工作，为产品协同设计、网络化设计提供一致的知识体系。     

支持复杂产品系统设计的虚拟知识流生成算法

复杂产品系统设计流程环节多,设计人员不仅需要掌握本环节的知识,也需要了解相关环节的概要知识,采用本体表示的复杂产品系统知识资源对设计人员构成艰巨的挑战。结合工作流与本体技术,设计了满足设计人员知识需求的虚拟知识流生成算法。算法允许设计人员指定工作流各个节点的起始概念、属性关系以及知识深度,然后遍历各个节点生成各节点本体视图,形成支持设计人员知识需求的虚拟知识流,从而促进设计人员的知识共享。算法具有起始概念顺序无关性、属性指令累加性、完备性,计算时间随本体中概念数量线性增加。最后以飞机设计中的虚拟知识流为例说明了算法应用。     

基于大数据的产品族本体造型意象挖掘方法研究

为提升产品造型意象成族的准确性,增强感性工学研究中意象词汇提取的规范性和知识重用性。 首先从同族、泛族、异族的概念切入,对目标产品族的造型意象本体进行了定义;再借助 word2vec 工具和主 成分分析法(PCA)分别完成了对产品族意象词汇的关联性联想和降维提取,从而构建了意象词汇挖掘机制,通 过此机制可以辅助设计师利用网络大数据资源更高效、准确地进行目标产品意象的挖掘,一定程度上解决了传 统感性工学在意象挖掘方法中模糊性。最后结合意象词汇与造型特征的映射关系,利用 Protege 工具构建了产 品族造型意象的本体模型,对目标产品的造型意象知识进行了逻辑化表征,为下一代产品继承并发展原产品族 造型意象提供参考。以马自达 MX-5 车系的造型意象为例构建了本体模型,并进行了子代产品前脸的概念设计。     

Form design of product image using grey relational analysis and neural network models

This paper presents a new approach to determining the best design combination of product form elements for matching a given product image represented by a word pair. A grey relational analysis (GRA) model is used to examine the relationship between product form elements and product image, thus identifying the most influential elements of product form for a given product image. A grey prediction (GP) model and a neural network (NN) model are used individually and in conjunction with the GRA model, in order to predict and suggest the best form design combination. An experimental study on the form design of mobile phones is conducted to evaluate the performance of these models. Based on expert surveys, the concept of Kansei Engineering is used to extract and evaluate the experimental samples, and a morphological analysis is used to extract form elements from these sample mobile phones. The evaluation result shows that all the NN-based models outperform the GP-based models, suggesting that the NN model should be used to help product designers determine the best combination of form elements for achieving a desirable product image. The GRA model can be incorporated into the NN model to help designers focus on the most influential elements in form design of mobile phones.     

A user requirement driven framework for collaborative design knowledge management

In today’s competitive global marketplace and knowledge-based economy, user requirement becomes an important input information for enterprises to develop new product and a critical factor to drive product collaborative design evolution. Meanwhile, there remains no consensus on how best to support knowledge activities and significant challenges to establishing design information management facing to rapid collaborative product development with dynamic user requirement. This paper introduces solutions for designer to deal with dynamic user requirement information through requirement evaluation and prediction method. In this study, we propose a user requirements-oriented knowledge management concept that is based on a four level hierarchy map model with special regard to knowledge collaboration and information communication. Furthermore, a novel distributed concurrent and interactive user requirement database was constructed, and the framework driven by user requirement was put forward to support collaborative design knowledge management. Finally, the service robot design project of a start-up company is used as a case study to explain the implementation of proposed framework.     

Modeling decisions under uncertainty in adaptive user interfaces

The present work proposes a methodological approach for modeling adaptation decisions and for solving the problem of integrating existing as well as acquired knowledge in the decision module of an adaptive interface. So far, most applications do not exploit in full the value of data originating from user models or knowledge acquisition engines that monitor the user and the context. The proposed decision theoretic model is represented through specifically structured influence diagrams. It provides to designers and developers a specific method to encode user and context information, as well as other crucial decision factors, to be subsequently used in the decision making process regarding user interface adaptation actions. Such a process is driven by the definition of relevant utilities referring to the design of a user interface. The proposed model guides designers and developers of an adaptive or intelligent interface to integrate, without conflicts and incoherence, design strategies, design goals, user goals, alternative constituents, user profile, context and application domain knowledge. An illustrative example of the analyzed modeling method is presented.

Research on digital characterization and identification process model of functional genes for intelligent innovative design

The inheritance and variation of functional knowledge is an important way to achieve product innovation. Analogous biological genetic inheritance can solve the problems with the inheritance and variation of functional knowledge. However, the different expressions of functional knowledge in different domains lead designers to consuming a lot of time for functional knowledge characterization and identification, which reduces the efficiency of functional knowledge application. Therefore, in order to solve the problem of inefficient application of functional knowledge in the genetic process caused by irregular expression of functional knowledge, the paper proposes a digital characterization and identification process model of functional genes for product intelligent innovative design. The process model enables product intelligent innovative design through digital characterization of functional genes and rapid identification of functional genes using computer assistance. The process model consists of four following steps. First, extract functional knowledge from patents and perform preliminary functional gene characterization. Second, characterize functional genes digitally by using computerized digital coding techniques. Third, identify the required functional genes by using image similarity matching algorithm. It assists designers to quickly identify the functional genes required for the target system. Fourth, obtain the target product design scheme. By “transcribing” and “translating” the required functional genes and using TRIZ tools to solve the translated scheme, the product innovative design scheme is finally obtained. The feasibility and effectiveness of the model are verified by the intelligent innovative design of shared bicycle parking management device.     

Visual product evaluation: exploring users' emotional relationships with products

This paper discusses an industrial designer's approach to eliciting user perceptions and emotional responses to products through visual evaluation and stimuli. Whilst the authors accept that product functionality is crucial for product success, the appearance, use of materials, shape and form provide the most immediate product data for the user. Less tangible issues such as emotional bonding of users with products, cultural perceptions and social value systems, provide valuable insights for the product developer to help expand knowledge and understanding of the users' need beyond the functional. This paper presents product personality profiling as a new technique for design researchers/designers, and discusses it alongside other emerging approaches such as mood boards and visual product evaluation. The authors have used these techniques during focus group sessions with users to elicit individuals' needs and aspirations towards products. Such a user-centred approach is fundamental to applied ergonomics. Experiences, benefits, and limitations of these techniques are outlined as well as the opportunities for further development.