Cognitive information flow analysis

The cognitive information flow analysis (CIFA) is introduced as a method to integrate results from cognitive task and work analyses in order to provide a focus on the necessary system information flow, which includes how information is produced, consumed, and transformed by the various system functions and users. CIFA can be used as a tool to augment cognitive task and work analyses. This paper presents the CIFA technique, provides a case study that applies the CIFA method to existing goal-directed task analysis and modified cognitive work analysis results, and provides insight into CIFA’s use for informing the design of a human-robot system. CIFA augments the results provided by cognitive task and work analyses and can guide system design and development. CIFA differs from existing information flow techniques in that it allows representation of systems containing large numbers of users for highly complex and uncertain domains. Existing cognitive task and work analyses integration methods rely heavily on relational tables. CIFA specifically expresses the interconnectivity of the various system subcomponents, including partial ordering and parallelism, by fundamentally focusing on the information flow. CIFA also identifies both existing and potential, information bottlenecks and highlights teamwork.     

考虑质量价值水平的复杂产品供应链质量成本优化方法

优化复杂产品供应链质量成本是提高供应链质量管控能力、降低供应链质量风险的重要方法.综合考虑产品质量水平和产品研制成本,提出复杂产品质量价值概念,并详细分析以供应商网络为基础的复杂产品质量价值形成机理.建立复杂产品质量价值GERT网络模型,实现复杂产品质量价值水平的量化计算,并以此为基础,通过识别网络中的关键供应商建立优化模型,提出考虑质量价值水平的复杂产品供应链质量成本优化方法.最后通过算例验证模型方法的科学性和有效性.     

相关新产品的组合投入模型

为提高新产品开发的成功率,企业需要有效的决策方法,以便开发新产品创意,并把新产品成功地引入市场.首先引入新产品最佳投入期和相关收益的概念,在产品生命周期量化描述前提下,提出一个非线性半无限规划的相关新产品组合投入模型.并用改进遗传算法(GA)求解.最后给出的数值例子及其在不同条件下的最好解说明,相关新产品的组合投入模型具有较强的实用性.     

生鲜农产品冷链物流低碳配送路径优化研究

综合考虑配送车辆的固定成本、运输成本、生鲜农产品的货损成本、制冷成本、配送过程中产生的碳排放成本，以及因未满足客户要求的服务时间窗而产生的惩罚成本作为目标函数，构建考虑碳排放的生鲜农产品配送路径优化模型，提出了解决该问题的一种结合2-opt局部搜索机制的改进蚁群算法，并用实例对模型及算法的有效性进行验证，同时对算法参数进行了敏感性分析。仿真实验及算法对比结果证明模型和算法是有效的，可以为物流企业的配送决策提供参考。     

A multi-objective optimization model for process targeting using sampling plans

The process targeting problem is usually formulated as a single objective optimization model. In this paper, a multi-objective optimization model is developed for the process targeting problem. The process under consideration produces a product with a normally distributed quality characteristic with unknown mean and known variance. The quality characteristic has a lower specification limit. The quality of the product is controlled via lot-by-lot acceptance sampling. The objectives used in the model are to maximize profit, income and product uniformity using the Taguchi quadratic loss function as a surrogate for product uniformity. An algorithm is proposed to obtain and rank the set of Pareto optimal points. The utility of the model is demonstrated using a numerical example from the literature. Sensitivity analysis on the model parameters showed that the results of the model are sensitive to changes in process variance. In addition, the optimal objectives of the profit function and product uniformity are more sensitive to changes in model parameters than the income function.     

Do-it-yourself as a means for making assistive technology accessible to elderly people: Evidence from the ICARE project

New assistive technology (AT) is at our disposal for improving the everyday life of people in need. Yet, the current way how AT is produced and provisioned is hindering certain marginalised groups in the population, particularly elderly people, to get access to it. To expedite time-to-market, reduce costs, and increase accessibility to otherwise unattainable AT, we explore if do-it-yourself (DIY) could be a feasible and desirable alternative to commercial applications. We provide answers to the following research questions: (1) For whom does the DIY approach work in the context of assistive technology? (2) Under which circumstances do DIY work? and (3) How can researchers make DIY a satisfying experience? The evidence we collected during the “iCare” project suggests that DIY attracts both, elderly people with a need-based motive and a hedonic motive. It also shows that a participatory approach and an early engagement with potential users, their family members, and informal caregivers is beneficial for improving design and use-related aspects of the AT and the DIY intervention.     

Deterministic inventory lot-size models with shortages for fluctuating demand and unit purchase cost

The classical economic order quantity (EOQ) model assumes not only a constant demand rate but also a fixed unit purchasing cost. In today's time‐based competition, the unit cost of a high‐tech product declines significantly over its short product life cycle while its demand increases. Therefore, using the classical EOQ formulation for a high‐tech product will cause varying magnitudes of error. In addition, the cost of purchases as a percentage of sales is often substantial. Consequently, adding the purchasing strategy into the EOQ model is vital. In this paper, we assume that not only the demand function but also the unit purchase cost is fluctuating with time. We then provide an easy‐to‐use algorithm to find the optimal replenishment number and schedule. In a numerical example, we show that the total cost obtained by our proposed model is 32.4% less expensive than that obtained by the classical EOQ model.     

DIY-CDR: an ontology-based, Do-It-Yourself component discoverer and recommender

The do-it-yourself (DIY) culture has been continuously articulated since mid-1920s. The DIY spirit gets gradually spread because people realize that DIY activities are a way to confirm their personal creativities, outsource results, and expand their social contacts. We are motivated to design and implement a computing environment to support users to DIY their personalized Internet-of-things (IoT) applications. Before a person starts his DIY processes, it is important for him to find proper components that meet his needs. This article records our recent results concerning how to automatically discover and recommend existing components to users. The controlled fully automated ontology-assisted matching strategy (C-FOAM) is a matching strategy that contains algorithms at three different levels—string, lexical, and conceptual (or graphical). In this paper, we extend C-FOAM and embed it in a component discovery and recommendation module, which is called do-it-yourself component discoverer and recommender (DIY-CDR). DIY-CDR also uses semantic decision tables (SDT) to gather user specific decision rules and set up parameters for C-FOAM.     

A game theory-based model for product portfolio management in a competitive market

In today’s competitive markets, effective product portfolio is critical for manufacturers that offer several products. From manufacturers’ perspective, the diversity must be maintained in a level in which the engineering costs do not exceed the acquired advantages of increased market share. On the other hand, product portfolio diversity is prominent for customers. In addition, manufacturers should always be careful about competitors activity. Therefore, we consider the problem of product portfolio management (PPM) in a competitive environment. This paper constructs a game theory-based mathematical model to deal with this new PPM problem. In this presented mathematical model, the PPM problem is formulated as a 2-person non-cooperative game with complete information. Each player has a set of strategies which correspond to the feasible product portfolios. Every payoff is determined by the procedure that considers the customer–engineering interaction in product portfolio planning, which aims to optimize product portfolio for a target market segment, and proposed a maximizing surplus share model for it. Therefore, obtaining the optimal product portfolio is determined by the Nash equilibrium point of this game. Finally, a numerical example is presented to demonstrate the feasibility of the approach.     

Product mix problems considering several probabilistic conditions and flexibility of constraints

This paper considers product mix problems including randomness of future returns, ambiguity of coefficients and flexibility of upper value with respect to each constraint such as budget, human resource, time and several costs. Particularly, the flexibility is assumed to be a fuzzy goal. Then, several models based on maximizing total future profits under a level of satisfaction to each fuzzy goal are proposed. Furthermore, the model considering preference ranking to each fuzzy goal of constraints is proposed. Since these problems are basically formulated as nonlinear programming problems, the transformations into deterministic equivalent problems are introduced and the efficient solution methods are developed. A numerical example for product mix problem is given to illustrate our proposed models.     

基于多层次GERT 的复杂产品研制进度规划“超冲突均衡”博弈模型

针对复杂产品研制进度规划中各级供应商与主制造商之间复杂的工作联系和博弈关系,基于复杂产品多层次研制网络,构建复杂产品研制多层次GERT网络模型,求解产品研制总进度与各级供应商进度的函数关系.进而分析博弈主体之间帕累托均衡、纳什均衡等多种均衡关系,建立进度规划的超冲突均衡博弈模型.通过算倒表明了所提出方法的有效性和实用性.     

基于具有自适应分段损失函数支持向量机的产品销售预测模型

针对产品销售时序包含噪声的数据特征, 提出一种基于自适应分段损失函数的支持向量机模型(AS??-SVM). AS??-SVM 为每个样本点赋一个单独的不敏感损失值, 以此降低模型对包含较大噪声的样本点的依赖性, 并从理论上证明了该方法可增强模型部分的泛化性能. 将AS??-SVM 与??-SVM 共同应用于处理一个数值算例和一个汽车销售预测实例中, 仿真实验结果表明, AS??-SVM 是有效可行的, 可获得比??-SVM 更精确的预测结果.

     

考虑偏好不确定的合作性单元制造优化研究

企业为加速产品的迭代更新,可采取合作生产及研发制造一体化的战略。该研究在产品设计方面考虑顾客偏好的动态变化和竞争产品的影响,在生产方面引入单元化制造资源合作共享思想。通过建立考虑顾客偏好不确定的合作性单元制造模型,以最大化单位成本所带来的顾客效用为目标,提升消费者福祉。提出了混合候鸟优化算法(HMBO)进行求解,并将它与经典候鸟优化算法(MBO)和模拟退火算法(SA)进行了比较。算例及大量数值实验验证了该方法的正确性和合理性,结果表明在相同运行时间内HMBO优于MBO和SA。     

Channel coordination with price discount mechanism under price‐sensitive market demand

This paper considers a two‐echelon supply chain with single vendor single buyer for trading a single product. The buyer's demand has been assumed to be price‐sensitive. We have assumed three‐level inspection at the vendor's end in order to maintain good quality of the items delivered to the buyer. We have developed models for both decentralized and centralized scenarios and have determined the optimal solution using the basic concepts of analytic geometry and algebra. In addition, we have proposed a price discount mechanism, where the vendor has provided discounts on the purchase cost to the buyer against the buyer's (increased) order quantity. Finally, in order to illustrate and validate the proposed model, a numerical example and sensitivity analysis is carried out, which has provided some important managerial implications. It has been observed from the numerical study that the proposed price discount policy coordinates the supply chain and has improved the profitability of the supply chain and its members.     

低碳环境下闭环供应链网络设计多目标鲁棒模糊优化问题

针对低碳环境下多级闭环供应链网络设计的战略定位和配置问题,综合考虑网络参数的模糊性以及多产品流,以供应链网络的总成本和总碳排放最小为目标,建立多目标鲁棒模糊优化模型.该模型将机会约束的最低置信水平作为决策变量,实现目标函数期望值、最优鲁棒性和可行鲁棒性之间的有效平衡.最后,设计一种基于必要性测度的交互式$\varepsilon$约束模糊求解方法,并通过算例验证所提模型和算法的有效性和可行性.     

Cost allocation model for optimizing supply chain inventory with controllable lead time

The coordination issue of a decentralized supply chain composed of a vendor and a buyer is considered in this paper. The vendor offers a single product to the buyer and the lead time can be controllable with adding crashing cost. Two supply chain inventory models with controllable lead time under different decision modes are considered, one is proposed under decentralized model based on Stackelberg model, the other is proposed under centralized model of the integrated supply chain. The solution procedures are also suggested to get the optimal solutions of these two models. In addition, an asymmetric Nash bargaining model based on satisfaction level is also developed to get the best cost allocation ratio between the vendor and the buyer by taking their individual rationalities into consideration. The results of numerical example show that shortening lead time reasonably can reduce inventory cost and the cost allocation model based on satisfaction level developed in this paper is effective.     

Group multi-criteria design concept evaluation using combined rough set theory and fuzzy set theory

Design concept evaluation is a critical stage in the product development which has significant impact on the downstream process in product development thus on success of new product. Design concept evaluation is widely recognized as a complex multi-criteria decision-making (MCDM) problem involving various decision criteria and large amount of data which are usually imprecise and subjective. This paper proposes a new decision-making method to evaluate product design concepts based on the distance between interval vectors each alternative and positive and negative ideal reference vectors. Rank of design concepts is obtained by calculating interval-based relative closeness index for each alternative. In this method, to deal with uncertainty and vagueness of data in the primary phases of product design, performance of design concepts with respect to quantitative and qualitative criteria are concurrently evaluated using rough set and fuzzy set. The weights of criteria used in the evaluation are obtained using the extent analysis method on fuzzy AHP. The efficacy of the method is demonstrated with a numerical example and the results are compared to TOPSIS method. In final, the conclusions of our method are represented and some future directions are proposed to improve the model.     

ℋ ∞ model reduction for linear parameter-varying systems with distributed delay

This paper is concerned with the ?_∞ model reduction for linear parameter-varying (LPV) systems with both discrete and distributed delays. For a given stable system, our attention is focused on the construction of reduced-order models, which approximate the original system well in an ?_∞ norm sense. First, a sufficient condition is proposed for the asymptotic stability with an ?_∞ performance of the error system by using the parameter-dependent Lyapunov functional method. Then, the decoupling technique is applied, such that there does not exist any product term between the Lyapunov matrices and the system matrices in the parametrised linear matrix inequality (PLMI) constraints; thus a new sufficient condition is obtained. Based on the new condition, two different approaches are developed to solve the model reduction problem. One is the convex linearisation approach and the other is the projection approach. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed design method.     

Exploring the effectiveness of commercial and custom-built games for cognitive training

There is increasing interest in quantifying the effectiveness of computer games in non-entertainment domains. We have explored general intelligence improvements for participants using either a commercial-off-the-shelf (COTS) game, a custom do-it-yourself (DIY) training system for a working memory task or an online strategy game to a control group (without training). Forty university level participants were divided into four groups (COTS, DIY, Gaming, Control) and were evaluated three times (pre-intervention, post-intervention, 1-week follow-up) with three weeks of training. In general intelligence tests both cognitive training systems (COTS and DIY groups) failed to produce significant improvements in comparison to a control group or a gaming group. Also neither cognitive training system produced significant improvements over the intervention or follow-up periods.