International Series in Operations Research & Management Science Volume 252 Series Editor Camille C. Price Stephen F. Austin State University, TX, USA Associate Series Editor Joe Zhu Worcester Polytechnic Institute, MA, USA Founding Series Editor Frederick S. Hillier Stanford University, CA, USA More information about this series at http://www.springer.com/series/6161
Tsan-Ming Choi Jianjun Gao James H. Lambert Chi-Kong Ng Jun Wang Editors Optimization and Control for Systems in the Big-Data Era Theory and Applications 123
Editors Tsan-Ming Choi Institute of Textiles and Clothing The Hong Kong Polytechnic University Hung Hom, Kowloon, Hong Kong James H. Lambert Department of Systems and Information Engineering University of Virginia Charlottesville, VA, USA Jun Wang Department of Management Science and Engineering, Business School Qingdao University Shandong, People s Republic of China Jianjun Gao School of Information Management and Engineering Shanghai University of Finance and Economics Shanghai, People s Republic of China Chi-Kong Ng Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Shatin, N.T., Hong Kong ISSN 0884-8289 ISSN 2214-7934 (electronic) International Series in Operations Research & Management Science ISBN 978-3-319-53516-6 ISBN 978-3-319-53518-0 (ebook) DOI 10.1007/978-3-319-53518-0 Library of Congress Control Number: 2017937015 Springer International Publishing AG 2017 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations. Printed on acid-free paper This Springer imprint is published by Springer Nature The registered company is Springer International Publishing AG The registered company address is: Gewerbestrasse 11, 6330 Cham, Switzerland
Preface Nowadays, for both business operations and engineering applications, there are huge amounts of data that can overwhelm computing resources of large-scale systems. These big data provide new opportunities to improve decision making and address risk for individuals as well as organizations. For example, the presence of market and sales data will yield better inventory planning for retail companies; massive and timely financial data will help improve portfolio management; the security holes of the Internet and the availability of data affect cryptography and privacy. Undoubtedly, utilizing big data smartly can enhance decision making. However, how to use and incorporate data into the decision making framework to yield a scientifically sound optimal decision is a challenging topic. Motivated by the importance of big data and the respective challenges in optimization and control, we have compiled and developed this edited volume on scientific innovations and reviews in optimization, control, and resilience management in the big data era. This book includes several important parts, namely, (1) Reviews on Optimization and Control Theories, (2) Reviews on Optimization and Control Applications, (3) Financial Optimization Analysis, (4) Operations Analysis, and (5) Concluding Remarks. All the featured papers are peer-refereed, and the specific topics covered include the following: Optimization and control for systems in the big data era: an introduction Dual control in big data era Time inconsistency and self-control optimization Quadratic convex reformulations for integer and mixed-integer quadratic programs Measurements of financial contagion Asset-liability management in continuous time Modern cryptography from the World War II era to the big data era Supply risk in the new business era A parameterized method for optimal multi-period portfolio selection v
vi Preface Sparse and multiple risk measures approach for data-driven portfolio optimization Multistage optioned portfolio selection Multi-period portfolio selection with stochastic investment horizon A new model and method for order selection problems in flow-shop production Quick response fashion supply chains in the big data era Optimization and control for systems in the big data era: concluding remarks and future research. We would like to take this opportunity to express our hearty thanks to Matthew Amboy and John Wolfe of Springer for their kindest support. We are indebted to all the reviewers who have provided timely review reports on the manuscripts. We are grateful for all the authors who have contributed their important and interesting research to this book. This book is dedicated to our mentor Professor Duan Li, the Patrick Huen Wing Ming Professor of Systems Engineering and Engineering Management at The Chinese University of Hong Kong, to honor his great achievements in both systems control and optimization and celebrate his 65th birthday in July 2017. In the bottom of our hearts, he is always a distinguished scholar, a kind gentleman, an excellent professor, and an outstanding teacher. We are very proud of being his students. As a remark, the royalty received by the editorial team from this book project is 100% fully donated to Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong. Hung Hom, Kowloon, Hong Kong Shanghai, People s Republic of China Charlottesville, VA, USA Shatin, N.T., Hong Kong Shandong, People s Republic of China November 2016 Tsan-Ming Choi, PhD Jianjun Gao, PhD James H. Lambert, PhD Chi-Kong Ng, PhD Jun Wang, PhD
Contents 1 Optimization and Control for Systems in the Big Data Era: An Introduction... 1 Tsan-Ming Choi, Jianjun Gao, James H. Lambert, Chi-Kong Ng, and Jun Wang Part I Reviews on Optimization and Control Theories 2 Dual Control in Big Data Era: An Overview... 9 Peilin Fu 3 Time Inconsistency and Self-Control Optimization Problems: Progress and Challenges... 33 Yun Shi and Xiangyu Cui 4 Quadratic Convex Reformulations for Integer and Mixed-Integer Quadratic Programs... 43 Baiyi Wu and Rujun Jiang Part II Reviews on Optimization and Control Applications 5 Measurements of Financial Contagion: A Primary Review from the Perspective of Structural Break... 61 Xi Pei and Shushang Zhu 6 Asset-Liability Management in Continuous-Time: Cointegration and Exponential Utility... 85 Mei Choi Chiu 7 A Review of Modern Cryptography: From the World War II Era to the Big-Data Era... 101 Bojun Lu vii
viii Contents 8 Modeling Supply Risk in the New Business Era: Supply Chain Competition and Cooperation... 121 Xiang Li, Yongjian Li, and Linghua Zhao Part III Financial Optimization Analysis 9 A Parameterized Method for Optimal Multi-Period Mean-Variance Portfolio Selection with Liability... 147 Xun Li, Zhongfei Li, Xianping Wu, and Haixiang Yao 10 Sparse and Multiple Risk Measures Approach for Data Driven Mean-CVaR Portfolio Optimization Model... 167 Jianjun Gao and Weiping Wu 11 Multistage Optioned Portfolio Selection: Mean-Variance Model and Target Tracking Model... 185 Jianfeng Liang 12 Multi-Period Portfolio Selection with Stochastic Investment Horizon... 217 Lan Yi Part IV Operations Analysis 13 A New Model and Method for Order Selection Problems in Flow-Shop Production... 245 Jun Wang, Xiaoxia Zhuang, and Baiyi Wu 14 Quick Response Fashion Supply Chains in the Big Data Era... 253 Tsan-Ming Choi Part V Concluding Remarks 15 Optimization and Control for Systems in the Big Data Era: Concluding Remarks... 271 Tsan-Ming Choi, Jianjun Gao, James H. Lambert, Chi-Kong Ng, and Jun Wang Index... 277
Contributors Mei Choi Chiu Department of Mathematics and Information Technology, The Education University of Hong Kong, Tai Po, Hong Kong Tsan-Ming Choi Institute of Textiles and Clothing, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong Xiangyu Cui School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, People s Republic of China Peilin Fu Department of Applied Engineering, School of Engineering and Computing, National University, San Diego, CA, USA Jianjun Gao School of Information Management and Engineering, Shanghai University of Finance and Economics, Shanghai, People s Republic of China Rujun Jiang Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong James H. Lambert Department of Systems and Information Engineering, University of Virginia, Charlottesville, VA, USA Xiang Li College of Economic and Social Development, Nankai University, Tianjin, People s Republic of China Xun Li Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China Yongjian Li Business School, Nankai University, Tianjin, People s Republic of China Zhongfei Li Department of Finance and Investment, Sun Yat-Sen Business School, Sun Yat-Sen University, Guangzhou, China Jianfeng Liang Department of Finance, Lingnan (University) College, Sun Yatsen University, Guangzhou, People s Republic of China ix
x Contributors Bojun Lu Portfolio Management Department, Foresea Life Insurance Co., Ltd., Shenzhen, China Chi-Kong Ng Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, N.T., Hong Kong Xi Pei Department of Finance and Investment, Sun Yat-Sen Business School, Sun Yat-Sen University, Guangzhou, China Yun Shi School of Management, Shanghai University, Shanghai, People s Republic of China Jun Wang Department of Management Science and Engineering, Business School, Qingdao University, Shandong, People s Republic of China Baiyi Wu School of Finance, Guangdong University of Foreign Studies, Guangzhou, People s Republic of China Weiping Wu Department of Automation, Shanghai Jiao Tong University, Shanghai, People s Republic of China Xianping Wu School of Mathematical Sciences, South China Normal University, Guangzhou, China Haixiang Yao School of Finance, Guangdong University of Foreign Studies, Guangzhou, China Lan Yi Management School, Jinan University, Guangzhou, People s Republic of China Linghua Zhao College of Economic and Social Development, Nankai University, Tianjin, People s Republic of China Shushang Zhu Department of Finance and Investment, Sun Yat-Sen Business School, Sun Yat-Sen University, Guangzhou, China Xiaoxia Zhuang Department of Management Science and Engineering, Business School, Qingdao University, Shandong, People s Republic of China