专栏首页数据魔术师IJPR特刊邀稿| 主题:生产和配送管理中的大数据分析

IJPR特刊邀稿| 主题:生产和配送管理中的大数据分析

International Journal of

Production Research

The International Journal of Production Research (IJPR), published since 1961, is a well-established, highly successful and leading journal reporting manufacturing, production and operations management research.

01

Call for Papers

Production and distribution are two key operational functions in a supply chain, which are interrelated as the latter can only start after the last task of a production process is completed. These two operational-related problems, which are solved separately or in an integrated way, have attracted considerable attention in the past five decades. However, existing studies usually assume that model parameters, be they certain or uncertain, are predefined.

We are now in the big data era. More and more companies and organizations are employing big data-related technologies, including information and communications technology (ICT), enterprise resources planning (ERP) systems, cloud computing, Internet of things, and social media, in their operations. All these sensor-based and computing systems store and manipulate massive amounts of data. The abundant available data together with big data analytics techniques offer unprecedented opportunities to enhance production and distribution management. How to apply big data analytics techniques to support production and distribution management is not only vital, but also challenging since data are often heterogeneous and diversified, and require huge storage and speedy processing.

This special issue seeks to provide a platform to facilitate interactions between researchers and practitioners in dig data analytics for production and distribution management. We welcome papers that make impactful contributions in terms of methodological advances or modelling innovativeness in addressing significant and well-motivated issues related to the theme.

02

Topics of Interest

Papers can be theoretical, methodological, computational, or application-oriented. Potential topics include, but are not limited to, the following:

  • Identifying the limitations of the current big data analytics techniques and strategies for production and distribution management, and proposing improvements;
  • Conducting data analysis at all stages from production to distribution;
  • Developing new models or theories for dig data analytics for production and distribution management;
  • Comparing classical operational optimization-based and data-driven approaches for the models of production and distribution management;
  • Exploring new models for production and distribution management in different contexts (e.g., Industry 4.0, green manufacturing, green logistics, and last-mile delivery)

Editors

Yunqiang Yin School of Management and Economics, University of Electronic Science and Technology of China, Chengdu, China;yinyq@uestc.edu.cn

Feng Chu,

Laboratory IBISC, Univeristy of Evry Val d’Essonne, France; feng.chu@univ-evry.fr

Alexandre Dolgui,

Centre for Industrial Engineering and Computer Science, Ecole des Mines des Saint Etienne, Saint Etienne, France; alexandre.dolgui@imt-atlantique.fr

T.C.E. Cheng,

Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong; edwin.cheng@polyu.edu.hk

M.C. Zhou,

Helen and John C. Hartmann Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ 07102, USA; zhou@njit.edu

---------- END ----------

本文分享自微信公众号 - 数据魔术师(data-magician),作者:殷允强

原文出处及转载信息见文内详细说明,如有侵权,请联系 yunjia_community@tencent.com 删除。

原始发表时间:2020-01-17

本文参与腾讯云自媒体分享计划,欢迎正在阅读的你也加入,一起分享。

我来说两句

0 条评论
登录 后参与评论

相关文章

  • 带容量约束的弧路径问题(CARP)简介

    路径问题的研究可以分为两个方向:以点为服务对象的车辆路径问题(VRP)和以弧为服务对象的弧路径问题(ARP)。不同于前者,ARP的基本特征是车队从一个仓库出发,...

    用户1621951
  • 车辆路径规划中的Dial A Ride 问题简介

    今天我们给大家带来的是Dial a ride问题(DAR)的介绍,文中所用资料多参考于文献。先上目录

    用户1621951
  • INFORMS TSL Best Paper Award2020

    The Institute for Operations Research and the Management Sciences

    用户1621951
  • ACL 2018 计算语言学协会接受论文列表

    WZEARW
  • 乳腺癌预后基因集

    In addition to cell of origin and somatic mutation events, studies over the past...

    生信技能树
  • 用于NLP的Python:使用Keras进行深度学习文本生成

    文本生成是NLP的最新应用程序之一。深度学习技术已用于各种文本生成任务,例如写作诗歌,生成电影脚本甚至创作音乐。但是,在本文中,我们将看到一个非常简单的文本生成...

    拓端
  • 促进包容性获取丰富在线内容和服务的策略研究

    中文摘要:在线访问内容和服务对每个人,包括残疾人,都越来越重要。包括《美国残疾人法》在内的各国承诺,以及包括《联合国残疾人权利宣言》在内的国际决议,都要求努力确...

    用户7454122
  • 机器学习研究和开发所需的组件列表

    Here is a list of components that are needed for the successful machine learning...

    iOSDevLog
  • 深度学习与TensorFlow:FCN论文翻译(三)

    We test our FCN on semantic segmentation and scene parsing, exploring PASCAL VOC...

    云时之间
  • Github项目推荐 | 知识图谱文献集合

    https://github.com/shaoxiongji/awesome-knowledge-graph

    AI研习社

扫码关注云+社区

领取腾讯云代金券