Discrete Dynamics in Nature and Society

Discrete Optimization for Dynamic Systems of Operations Management in Data-Driven Society


Publishing date
01 Apr 2019
Status
Published
Submission deadline
30 Nov 2018

Lead Editor

1Shanghai University, Shanghai, China

2The Hong Kong Polytechnic University, Hung Hom, Hong Kong

3Chalmers University of Technology, Gothenburg, Sweden

4Mississippi State University, Starkville, USA


Discrete Optimization for Dynamic Systems of Operations Management in Data-Driven Society

Description

Society is being reshaped by large volumes of data generated from the Internet of Things, smart devices, and dynamic human-to-machine communications. Big data is playing a transformative role in this new era, while also enabling a data-driven society. As such, data-driven decision methodology is becoming increasingly important for operation managers when handling dynamic issues. Various data-driven systems with well-designed models, as well as algorithms developed by high-tech software providers (and consulting companies), are now replacing traditional decision-making based predominantly on managers’ experiences. Among these emerging decision systems, most rely upon discrete optimization models. For these “smart” data-driven systems, the core issue lies in the design of the discrete optimization models for handling dynamic features contained in operations management (OM) activities.

In recent decades, various discrete optimization techniques have been employed by managers and management scientists to improve the performance of dynamic OM systems. With the rapid growth in computational technologies, including data mining technologies, discrete event simulation techniques, and intelligence algorithms, OM relies more and more on optimal solutions (or their approximates) based on high-performance models and algorithms.

Now, we are delighted to welcome interested authors to submit to this special issue, which will gather the most recent achievements in this rapidly evolving field. Its goal is to publish high-quality research papers as well as review articles that address recent advances in models and algorithms concerning discrete optimizations on dynamic OM systems relevant to our data-driven society.

Potential topics include but are not limited to the following:

  • Discrete optimization methodologies for stochastic OM problems
  • System dynamics in behavior OM for M-Commerce
  • Discrete optimization models for strategic-level OM decision-making
  • Heuristics and metaheuristics for high-efficiency OM decision-making under uncertain conditions
  • Data-driven risk analysis and modeling for OM decisions in dynamic contexts
  • Dynamic programming based exact methods for stochastic OM problems
  • Discrete optimization models and algorithms for green OM
  • Advanced modeling and optimization techniques for data-driven dynamic OM problems
  • New data-driven models for dynamic closed-loop supply chain management

Articles

  • Special Issue
  • - Volume 2019
  • - Article ID 4037859
  • - Research Article

Adopting a QCA Approach to Investigating the Risks Involved in Megaprojects from Auditing Perspective

Liang Ma | Bing Zhang | ... | Ruoyu Jin
  • Special Issue
  • - Volume 2019
  • - Article ID 4769870
  • - Research Article

Research on Supply Chain Coordination Based on Block Chain Technology and Customer Random Demand

Yongfei Li | Bill Wang | Dong Yang
  • Special Issue
  • - Volume 2019
  • - Article ID 2493638
  • - Research Article

Simulation Optimization of Discrete Logistics Processes: A Case Study on Logistics of an E-Commerce Enterprise in Shanghai

Xiang Xu | Yue Li | Ruiyun Tang
  • Special Issue
  • - Volume 2019
  • - Article ID 2615154
  • - Research Article

A Metaheuristic Algorithm to Transporter Scheduling for Assembly Blocks in a Shipyard considering Precedence and Cooperating Constraints

Ning-Rong Tao | Zu-Hua Jiang | ... | Bai-He Li
  • Special Issue
  • - Volume 2019
  • - Article ID 7438147
  • - Research Article

Distance-Based Congestion Pricing with Day-to-Day Dynamic Traffic Flow Evolution Process

Qixiu Cheng | Jiping Xing | ... | Xiao Fu
  • Special Issue
  • - Volume 2019
  • - Article ID 8239047
  • - Research Article

Applying Big Data Analytics to Monitor Tourist Flow for the Scenic Area Operation Management

Siyang Qin | Jie Man | ... | Xinquan Ge
  • Special Issue
  • - Volume 2018
  • - Article ID 1529058
  • - Research Article

An Improved Genetic Algorithm Based Robust Approach for Stochastic Dynamic Facility Layout Problem

Yunfang Peng | Tian Zeng | ... | Beixin Xia
  • Special Issue
  • - Volume 2018
  • - Article ID 8703852
  • - Research Article

Optimizing the Composite Cost Involved in Road Motor-Transporting Trucks by Taking into Account Traffic Condition

Hongying Fei | Chengyi Zhang
  • Special Issue
  • - Volume 2018
  • - Article ID 1917252
  • - Research Article

Optimal Scheme for Process Quality and Cost Control by Integrating a Continuous Sampling Plan and the Process Yield Index

Chunzhi Li | Shurong Tong | Keqin Wang
  • Special Issue
  • - Volume 2018
  • - Article ID 6783190
  • - Research Article

Data-Driven Recovery Potential Analysis and Modeling for Batteries Recovery Operations in Electric Bicycle Industry

Ping Zhang | Guangfu Liu
Discrete Dynamics in Nature and Society
 Journal metrics
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Acceptance rate13%
Submission to final decision127 days
Acceptance to publication23 days
CiteScore2.000
Journal Citation Indicator0.410
Impact Factor1.4
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