A performance evaluation framework of public health distribution network for essential medicines: lessons from the select Indian states

The present work has been carried out to develop a performance evaluation framework of distribution network design in public health with specific reference to essential medicines based on six different types of public health distribution networks (PHDNs) prevalent across six Indian states. We evaluated the performance of PHDNs on the criteria of cost and service and also on the sub-criteria of cost and service by following the analytic hierarchy process. We utilized the pairwise comparison method in determining the relative importance of criteria and sub-criteria by seeking responses from several experts and subsequently evaluated the PHDNs on all sub-criteria in a 7-point Likert scale by seeking views from the same experts. Finally, we developed the “cost–service matrix,” in which cost and service have been depicted in the horizontal and vertical axes, respectively. We demonstrated the performance of six PHDNs in this matrix in terms of cost and service by plotting scores obtained by them on cost and service, respectively. The findings of the study provide rich insights to the policy planners of public health.     

Simulation and analysis of edge ghosting for microcapsule e-paper based on particle dynamics and light scattering model

Electronic paper (e-paper) is a reflective display technology with unique advantages, such as bistability, low-power consumption, and high ambient contrast ratio. These features make e-paper a promising candidate for future Internet of Things applications. Among different technologies of e-paper, electrophoretic display (EPD) is the most successful one for commercialization. However, the edge ghosting (also known as the fringing effect) still limits the performance of EPD. Herein, we established a model of particle dynamics of electrophoresis, simulated the edge ghosting of microcapsule EPD, analyzed the edge ghosting effect, and revealed the relationship between thicknesses, dielectric constants of the back binder layer, and the edge ghosting. Two EPD panels with different thicknesses of back binder layer were demonstrated, which verifies the accuracy of this simulation model. With the proposed model, many device mechanisms and product issues can be analyzed and illustrated, which is supposed to guide the researchers in optimizing the device structure design of EPD.     

Coordinated scheduling of production and logistics for large-scale closed-loop manufacturing using Benders decomposition optimization

This paper studies coordinated scheduling of production and logistics for a large-scale closed-loop manufacturing system by integrating its manufacturing and recycling process. In addition to the forward manufacturing process, different recycling units in reverse recycling process are also studied. A decentralized network is designed to formulate the coordinated scheduling problem as a mixed integer programming model with both binary and integer variables. As the problem for closed-loop manufacturing is large-scale and computational-consuming in nature, the model is divided into integer variable sub-models and complex binary variable sub-models for preprocessing and reprocessing respectively. An iterative solution approach by Benders decomposition is developed to accelerate the solving efficiency in large-scale case by updating custom constraints. A case study is conducted to investigate the managerial implications of the decentralized network for the closed-loop manufacturing system. Computational experiments demonstrate the validity and efficiency of the proposed iterative solution approach for the large-scale scenarios.     

基于NS3-gym框架的智能干扰规避系统设计与实现

多智能体构建的无线通信网络在受到外部恶意干扰时,智能体需要与环境进行大量交互来学习干扰规律和优化抗干扰策略。为了有效模拟和验证智能体与外部干扰环境的学习交互过程,需要构建智能干扰规避仿真系统。提出了一种基于NS3-gym框架的智能干扰规避系统,NS3模拟智能通信网络场景并将感知到的网络状态数据作为智能体的输入,智能体对输入数据进行学习分析得到干扰规避决策,并通过gym与NS3之间的交互将其返回到NS3中的仿真网络进行抗干扰策略部署。NS3-gym框架提供了NS3和OpenAI gym之间进行信息交互的接口。在Ubuntu20.04系统下搭建了智能干扰规避系统的仿真平台,分别验证了Q学习算法以及WoLF-PHC算法在扫频干扰、贪婪随机策略干扰、跟随干扰、随机干扰四种场景下的抗干扰性能。仿真结果证明了所提系统架构与仿真平台的正确性和有效性。     

An energy-efficient multi-objective integrated process planning and scheduling for a flexible job-shop-type remanufacturing system

This study considers an energy-efficient multi-objective integrated process planning and scheduling (IPPS) problem for the remanufacturing system (RMS) integrating parallel disassembly, flexible job-shop-type reprocessing, and parallel reassembly shops with the goal of realizing the minimization of both energy cost and completion time. The multi-objective mixed-integer programming model is first constructed with consideration of operation, sequence, and process flexibilities in the RMS for identifying this scheduling issue mathematically. An improved spider monkey optimization algorithm (ISMO) with a global criterion multi-objective method is developed to address the proposed problem. By embedding dynamic adaptive inertia weight and various local neighborhood searching strategies in ISMO, its global and local search capabilities are improved significantly. A set of simulation experiments are systematically designed and conducted for evaluating ISMO’s performance. Finally, a case study from the real-world remanufacturing scenario is adopted to assess ISMO’s ability to handle the realistic remanufacturing IPPS problem. Simulation results demonstrate ISMO’s superiority compared to other baseline algorithms when tackling the energy-aware IPPS problem regarding solution accuracy, computing speed, solution stability, and convergence behavior. Meanwhile, the case study results validate ISMO’s supremacy in solving the real-world remanufacturing IPPS problem with relatively lower energy usage and time cost.     

A digital twin in transportation: Real-time synergy of traffic data streams and simulation for virtualizing motorway dynamics

The introduction of digital twins is expected to fundamentally change the technology in transportation systems, as they appear to be a compelling concept for monitoring the entire life cycle of the transport system. The advent of widespread information technology, particularly the availability of real-time traffic data, provides the foundation for supplementing predominated (offline) microscopic simulation approaches with actual data to create a detailed real-time digital representation of the physical traffic. However, the use of actual traffic data in real-time motorway analysis has not yet been explored. The reason is that there are no supporting models and the applicability of real-time data in the context of microscopic simulations has yet to be recognized. Thus, this article focuses on microscopic motorway simulation with real-time data integration during system run-time. As a result, we propose a novel paradigm in motorway traffic modeling and demonstrate it using the continuously synchronized digital twin model of the Geneva motorway (DT-GM). We analyze the application of the microscopic simulator SUMO in modeling and simulating on-the-fly synchronized digital replicas of real traffic by leveraging fine-grained actual traffic data streams from motorway traffic counters as input to DT-GM. Thus, the detailed methodological process of developing DT-GM is presented, highlighting the calibration features of SUMO that enable (dynamic) continuous calibration of running simulation scenarios. By doing so, the actual traffic data are directly fused into the running DT-GM every minute so that DT-GM is continuously calibrated as the physical equivalent changes. Accordingly, DT-GM raises a technology dimension in motorway traffic simulation to the next level by enabling simulation-based control optimization during system run-time that was previously unattainable. It, thus, forms the foundation for further evolution of real-time predictive analytics as support for safety–critical decisions in traffic management. Simulation results provide a solid basis for the future real-time analysis of an extended Swiss motorway network.     

交叉口混合交通流微观控制模型

为构建智能网联汽车(CAV)和有人驾驶汽车(HDV)混合通行情况下的交叉口通行机制与控制方法, 本文提出CAV专用道条件下交叉口协同通行模型. 首先, 设计CAV专用道条件下的交叉口布置, 对交叉口进行网格化处理,将CAV通行时隙和HDV绿灯相位对交叉口某部分网格某时段的占用统一到交叉口时空资源描述框架下; 其次, 建立兼顾CAV与HDV的交叉口时空网格资源分配模型, 构建自适应信号灯控制算法和CAV轨迹规划算法; 再次, 以车辆最小延误为目标进行自适应信号灯配时优化和CAV轨迹优化; 最后, 选取广州某典型交叉口建立仿真实验对所提方法的有效性进行了验证.     

Heterogeneous clustering via adversarial deep Bayesian generative model

This paper aims to study the deep clustering problem with heterogeneous features and unknown cluster number. To address this issue, a novel deep Bayesian clustering framework is proposed. In particular, a heterogeneous feature metric is first constructed to measure the similarity between different types of features. Then, a feature metric-restricted hierarchical sample generation process is established, in which sample with heterogeneous features is clustered by generating it from a similarity constraint hidden space. When estimating the model parameters and posterior probability, the corresponding variational inference algorithm is derived and implemented. To verify our model capability, we demonstrate our model on the synthetic dataset and show the superiority of the proposed method on some real datasets. Our source code is released on the website: Github.com/yexlwh/Heterogeneousclustering.     

Strategic innovation through outsourcing – A theoretical review

Competition in the Information Technology Outsourcing (ITO) and Business Process Outsourcing (BPO) industry is increasingly moving from being motivated by cost savings towards strategic benefits that service providers can offer to their clients. Innovation is one such benefit that is expected nowadays in outsourcing engagements. The rising importance of innovation has been noticed and acknowledged not only in the Information Systems (IS) literature, but also in other management streams such as innovation and strategy. However, to date, these individual strands of research remain largely isolated from each other. Our theoretical review addresses this gap by consolidating and analyzing research on strategic innovation in the ITO and BPO context. The article set includes 95 papers published between 1998 and 2020 in outlets from the IS and related management fields. We craft a four-phase framework that integrates prior insights about (1) the antecedents of the decision to pursue strategic innovation in outsourcing settings; (2) arrangement options that facilitate strategic innovation in outsourcing relationships; (3) the generation of strategic innovations; and (4) realized strategic innovation outcomes, as assessed in the literature. We find that the research landscape to date is skewed, with many studies focusing on the first two phases. The last two phases remain relatively uncharted. We also discuss how innovation-oriented outsourcing insights compare with established research on cost-oriented outsourcing engagements. Finally, we offer directions for future research.     

Analysis of Critical Factors in Manufacturing by Adopting a Cloud Computing Service

The advantages of a cloud computing service are cost advantages, availability, scalability, flexibility, reduced time to market, and dynamic access to computing resources. Enterprises can improve the successful adoption rate of cloud computing services if they understand the critical factors. To find critical factors, this study first reviewed the literature and established a three-layer hierarchical factor table for adopting a cloud computing service based on the Technology-Organization-Environment framework. Then, a hybrid method that combines two multi-criteria decision-making tools—called the Fuzzy Analytic Network Process method and the concept of VlseKriterijumska Optimizacija I Kompromisno Resenje acceptable advantage—was used to objectively identify critical factors for the adoption of a cloud computing service, replacing the subjective decision of the authors. The results of this study determined five critical factors, namely data access security, information transmission security, senior management support, fallback cloud management, and employee acceptance. Finally, the paper presents the findings and implications of the study.