International Conference on Intelligent Transportation and Logistics with Big Data & 7Th International Forum on Decision Science

International Conference on Intelligent Transportation and Logistics with Big Data & 7th International Forum on Decision Science

26-29 July, 2019 Windsor, Ontario

Table of Contents

Sponsor List ...... 2

Organizing Committee ...... 3

Conference Location ...... 4

Conference at a Glance ...... 5

Plenary Sessions ...... 6

Parallel Sessions ...... 12

Sponsor List

Organizing Committee

Guoqing Zhang, Co-Chair

School of Engineering

University of Windsor, Canada

E-mail: [email protected]

Xiang Li, Co-Chair

School of Economic and Management

Beijing University of Chemical Technology, China

E-mail: [email protected]

Xiaofeng Xu, Organizing Chair

School of Economic and Management

China University of Petroleum, China

E-mail: [email protected]

Program Committee Members

Guoqing Yang, University of Windsor, E-mail: [email protected]

Mohammed Almanaseer, University of Windsor, E-mail: [email protected]

Jenny Yang, University of Windsor, E-mail: [email protected]

Volunteers

Hai Shen, Haijiao Li, Yuyu Chen, Jinrong Liu, Libin Guo, Breeze Fenton, Zhumiao Chen

Conference Location

2285 Wyandotte, Windsor, Ontario, Canada, N9B 1K3

Transportation during the conference

During the conference, we will provide a school bus between the hotels (Caesars Windsor, Best Western Plus Waterfront Hotel), the university and the dinner venue. The specific schedule is as follows.

Time Route

Saturday, July 27 Hotels → University of Windsor 8:20 am

Saturday, July 27 May Wah Inn Chinese Cuisine → Hotels 9:00 pm

Sunday, July 28 Hotels → University of Windsor 8:20 am Sunday, July 28 University of Windsor → Windsor River Cruises → Caesars Hotels (Walk) 6:10 pm or Best Western Plus Waterfront Hotel (Bus) Note: On Saturday evening, we will walk to dinner about 20 minutes.

Conference at a Glance

Plenary Sessions

SATURDAY 27 JULY Dr. Alexandre Dolgui is a Distinguished Professor (Full Professor of Exceptional Class in France) and the Head of Automation, Production and Computer Sciences Department at the IMT Atlantique (former Ecole des Mines de Nantes), France. His research focuses on manufacturing line design, production planning and supply chain optimization. He is the co-author of 5 books, the co-editor of 17 books or conference proceedings, the author of 225 refereed journal papers, 26 editorials, and 28 book chapters as well as over 400 papers in conference proceedings. He is the Editor-in-Chief of the International Journal of Production Research, an Area Editor of Computers & Industrial Engineering. He is Member of the Editorial Boards for 28 other journals. Dr. Dolgui has been responsible for the French national CNRS working group on Design of Production Systems (with about 336 individual members) and the regional project on Design and Management of Reconfigurable Manufacturing Systems.

Title: Optimal replenishment planning in assembly systems under uncertainties of component lead times

Abstract: Manufacturing firms use inventory management software, especially MRP, which ignored lead time uncertainty. It is true that in certain special cases, lead time uncertainty has essentially no effect and can be ignored. Nevertheless, more often, lead time fluctuations strongly degrade tools performance and cause high production costs, just as demand uncertainty does. Seemingly, uncertainty has been neglected for a long time in favor of studying demand uncertainties. Industry agrees that it is overdue and there is a need to rectify this oversight. Nowadays, this gap in research activity begins to be filled in order to respond to companies having non-deterministic lead-times constraints. A new approach of replenishment planning under uncertainty of lead times is proposed and a survey of our results is given.

Dr. Ali Diabat is a Global Network Professor of Logistics and Supply Chain Management at New York University. His research focuses on different applications of optimization and operations research. He has published over 100 research journal papers and over 30 conference papers in leading journals and international conference proceedings. Dr. Diabat has received 4 externally funded grants in the amount of about 3 million dollars from different industries, and more than $500,000 from internal and collaborative proposals funded by academic institutions. His industry experience includes working in the shipping industry, as an industrial engineer in Jordan, and as a business analyst in the United States. In addition, he held two positions as an operations research analyst in the banking and beverages industries, both in the United States. In 2014, he received the Best Faculty Research Award from the Department of Engineering Systems and Management at Masdar Institute. Dr. Diabat currently serves as an Associate Editor of the SME Journal of Manufacturing Systems (JMS) and as an Area Editor of the Journal of Computers and Industrial Engineering.

Title: Hub-and-spoke network design with interhub economies of scale and node congestion

Abstract: In this talk, we summarize the findings of two of our recent papers, both related to the design of hub- and-spoke networks taking into consideration interhub economies of scale and node congestion. In the canonical problem, a hub must be designated as a subset of nodes in the network, and flow emanating from all nodes must be routed through these hubs. Because cost savings due to flow consolidation may be counterbalanced by congestion costs at busy hubs, both aspects of the problem must be studied simultaneously. In the first paper, we consider the single-allocation version of the problem. Economies of scale are modelled through a piecewise- linear function that is concave in the total flow, while congestion penalties are modelled via outer approximations of non-linear convex functions. Lagrangian relaxation with a GRASP heuristic is used to solve the problem. In the second paper, the multiple allocation version is tackled. Here, both concave and convex costs are piecewise-linearized. A Benders decomposition approach is utilized with special attention paid to reducing the size of subproblem LPs. Computational studies confirm the value of the simultaneous modeling of concave and convex cost elements.

Dr. Ming Hu is a Professor of Operations Management at Rotman School of Management, University of Toronto and one of the 2018 Poets & Quants Best 40 Under 40 MBA Professors. His research has been featured in media such as Financial Times. Most recently, he focuses on operations management in the context of sharing economy, social buying, crowdfunding, crowdsourcing, and two-sided markets, with the goal to exploit operational decisions to the benefit of the society. He currently serves as the editor-in-chief of Naval Research Logistics, co-editor of a special issue of Manufacturing & Service Operations Management on sharing economy and innovative marketplaces, department co-editor of Service Science, and associate editor of Operations Research and Manufacturing & Service Operations Management, and senior editor of Production and Operations Management. He currently also serves as Vice Chair/Chair-Elect for the RM&P Section of INFORMS and Secretary/Treasurer for the MSOM Society of INFORMS.

Title: From the Classics to New Tunes: A Neoclassical View on Sharing Economy and Innovative Marketplaces

Abstract: Operations management has the tradition of coming from and going back to real-life applications. It deals with the management of the process of matching supply with demand. The emerging business process in a sharing economy or an innovative marketplace calls for active management from the operational perspective. We take a neoclassical perspective by drawing inspiration from the classic models in operations management and economics. We aim at building connections and identifying differences between those traditional models and the new applications in sharing economy and innovative marketplaces.

SUNDAY 28 JULY

Dr. Francisco Saldanha da Gama is a professor of Operations Research at the Department of Statistics and Operations Research at the Faculty of Science, University of Lisbon, where he received his Ph.D. in 2002. He has extensively published papers in scientific international journals mostly in the areas of location theory, supply chain management, logistics and combinatorial optimization. Together with Teresa Melo and Stefan Nickel, he has been awarded the EURO prize for the best EJOR review paper (2012) and the Elsevier prize for the EJOR top cited article 2007-2011 (2012), both with the paper entitled "Facility location and supply chain management: a review". He is a member of various international scientific organizations such as the EURO Working Group on Location Analysis of which he is one the past coordinators. Currently, he is the Editor- in-Chief of Computers & Operations Research.

Title: Logistics Network Design and Facility Location: The value of a multi-period stochastic solution

Abstract: In the past decades logistics network design has been a very active research field. This is an area where facility location and logistics are strongly intertwined, which is explained by the fact that many researchers working in Logistics address very often location problems as part of the strategic/tactical logistics decisions. Despite all the work done, the economic globalization together with the emergence of new technologies and communication paradigms are posing new challenges when it comes to developing optimization models for supporting decision making in this area. Dealing with time and uncertainty has become unavoidable in many situations.

In this presentation, different modeling aspects related with the inclusion of time and uncertainty in facility location problems are discussed. The goal is to better understand problems that are at the core of more comprehensive ones in logistics network design. By considering time explicitly in the models it becomes possible to capture some features of practical relevance that cannot be appropriately captured in a static setting; by considering a stochastic modeling framework it is possible to build risk-aware models. Unfortunately, the resulting models are often too large and thus hard to tackle even when using specially tailored procedures. This raises a query: is there a clear gain when considering a more involved model instead of a simplified one (e.g. deterministic or static)? In search for an answer to this question, several measures are discussed that include the value of a multi-period solution and the value of a risk-aware solution.

Dr. Jianping Li is a Distinguished Research Fellow at Chinese Academy of Sciences (CAS), and the director of the Institute of Systems Analysis and Management in Institutes of Science and Development, CAS. He has received the National Science Fund for Distinguished Young Scholars (2014). He serves as Executive Member and Secretary- General of the International Academy of Information Technology and Quantitative Management, Secretary-General of the Chinese Society of Optimization, Overall Planning and Economical Mathematics, Executive Editor-in-Chief of Chinese Journal of Management Science, etc. He was awarded the China Youth Science and Technology Award, the National Excellent Scientific and Technological Workers and the Excellent Tutor Award of Chinese Academy of Sciences. He has published 6 monographs and over 160 papers in leading journals and conferences/proceedings and granted 15 patents/software copyrights. In addition, he has won first-class Provincial or Ministry level scientific awards twice and first-class awards four times.

Title: Risk Identification and Integration Based on Textual Risk Disclosures

Abstract: Risk identification and integration are the two basic issues in the field of risk management. This report first introduces the three major problems of traditional data quality, and then introduces big data technology to comprehensively identify and reasonably integrate risks. Specifically, we use an unsupervised machine learning algorithm Sent-LDA to analyze the textual risk disclosures in the US listed energy company Form-10K statements, thereby constructing a hierarchical risk system for the energy industry; In addition, we propose a new semi-supervised algorithm called the Naive Collision Algorithm to identify banking risks and further integrate these risk combining traditional methods to obtain more reasonable risk integration.

Dr. Joe Zhu is a Professor of Operations Analytics in the Foisie School of Business at Worcester Polytechnic Institute, USA. He is an internationally recognized expert in methods of performance evaluation and benchmarking. He has published more than 15 books related to data envelopment analysis, and 140 peer-reviewed articles in journals such as Management Science, Operations Research, Sloan Management Review, IIE Transactions, Naval Research Logistics, European Journal of Operational Research, Journal of Operational Research Society, Annals of Operations Research, OMEGA, and others. In 2017, he is ranked No. 3 among the most productive and influential authors in 40 years of European Journal of Operational Research. He has more than 28,000 google scholar citations. He is an Area Editor of OMEGA and an Associate Editor of the Journal of Operational Research Society, and INFOR. He is also an editorial Board member of European Journal of Operational Research, and Computers & Operations Research. He is the Associate Series Editor for the Springer International Series in Operations Research and Management Science. He is a Japan Society for Promotion of

Science (JSPS) fellow and a William Evans Visiting Fellow (University of Otago, New Zealand). He is a Feng Tay Chair Professor (National Yunlin University of Technology and Science, Taiwan), and Chang Jiang Scholar Chair Professor awarded by the Ministry of Education of China.

Title: DEA under Big Data: Data Enabled Analytics and Network Data Envelopment Analysis

Abstract: This talk proposes that data envelopment analysis (DEA) should be viewed as a method (or tool) for data-oriented analytics. DEA is a data-driven tool for performance evaluation and benchmarking. While computational algorithms have been developed to deal with large volume of data (decision making units, inputs, and outputs) under the conventional DEA, valuable information hidden in big data that are represented by network structures should be extracted by DEA. These network structures, e.g., transportation and logistics systems, encompass a broader range of inter-linked metrics that cannot be modelled by the conventional DEA. It is shown that network DEA is different from the standard DEA, although it bears the name of DEA and some similarity with the conventional DEA. Network DEA is big Data Enabled Analytics (big DEA) when multiple (performance) metrics or attributes are linked through network structures. These network structures are too large or complex to be dealt with by the conventional DEA. Unlike the conventional DEA that are solved via linear programming, general network DEA corresponds to nonconvex optimization problems. This represents opportunities for developing techniques for solving non-linear network DEA models.

Parallel Sessions

Saturday, July 27 Paper ID Speaker Author Paper Title The Freight Transportation Intelligence and Shervin Espahbod Shervin Espahbod, 26 People-oriented Decisions: A Systematic Parallel Session 1: Wilfrid Laurier University, Haughton Intelligent transportation and [email protected] Literature Review logistics management Anjali Awasthi Rupinder Kaur, Cross-disciplinary Workforce Selection for 66 Concordia University, Anjali Awasthi Industry 4.0 [email protected] Session Chair: Dr. Anjali Customized Passenger Transport Service Awasthi Jiawei Gui Jiawei Gui, 71 Innovation for Intelligent Time: Evidence Time: 1:30 pm - 3:00 pm Chang’an University, Qunqi Wu [email protected] from Empirical Data in Siping Place: CEI 2101

Abdulnasser Abdulnasser Batch-Sizing and Machinability Data Elgaddar, Systems for Vertical Machining Center: 23 Elgaddar Abdelrahman Amer, Parallel Session 2: Optimal Cost of Quality and Environmental University of Windsor, Ahmed Azab, Big data technology and [email protected] Impact Fazle Baki methods in transportation Maheshan Maheshan Indraligngam, Indraligngam Benefits of Big Data in Supply Chain Session Chair: Dr. Abdulnasser 53 Mohamed Wahab, Ryerson University, Management Elgaddar maheshan.indralingam@ryer Mohamed Ismail, Time: 1:30 pm - 3:00 pm son.ca Liping Fang Place: CEI 2102 Amina Lamghari Bechir Ben Daya, Data Analysis Methods for Spring Street 61 Universite du Quebeca Jean-François Audy, Trois-Rivieres, Sweeping Logistics Amina Lamghari [email protected]

Xiaolei Guo 33 University of Windsor, Xiaolei Guo The Impact of Autonomous Vehicles on [email protected] Commute Ridesharing Hongguang Ma Hongguang Ma, Cooperative Game Analysis of Airport Bus Parallel Session 3: 34 Beijing University of Public transport and sharing Chemical Technology, Xiang Li and Taxi [email protected] economy Jiaming Liu, Jiaming Liu Bowen Zhang, The impacts of highway logistics Session Chair: Dr. Xiaolei Guo 35 Beijing University of Xiang Li, transportation network in China: A Chemical Technology, Xiande Zhao, complex network perspective Time: 1:30 pm - 3:00 pm [email protected] Place: CEI 2103 Liang Wang Parmis Emadi Parmis Emadi, Transportation Planning for Disaster Relief 50 University of Windsor, Zbigniew J Pasek Networks [email protected]

Saturday, July 27 Paper ID Speaker Author Paper Title Jianhua Ma, Jianhua Ma Weifeng Zhang, Third Party’s Extended Warranty Design 10 Shenzhen University, Yanchun Pan, Strategy in Supply Chain [email protected] Wen Yang Parallel Session 4: Cesar Augusto Cesar Augusto Coordination Via Revenue and Technology- Operation and supply chain Rodriguez Gallegos, 25 Rodriguez Gallegos cost Sharing in A Two-supplier and One- Qingguo Bai, management Concordia University, manufacturer Supply Chain System [email protected] Mingyuan Chen Session Chair: Dr. Jianhua Ma Re-routing and Planning of Maritime Suxiu Xu Suxiu Xu, Passenger Transport via Variable 17 Time: 3:20 pm - 5:50 pm Jinan University, Ting Qu Neighborhood Descent: The Case of Zhuhai [email protected] Place: CEI 2101 Islands

Haijiao Li Haijiao Li, Optimal Pricing Policy under Multi-period 45 Hunan University, Kuan Yang, University of Windsor, Setting with Strategic Consumers Guoqing Zhang [email protected]

Mahzan Dalawir, Mohammad Borooshan, Mahzan Dalawir Optimal Location and Sizing of Mobile 18 Abdelrahman Amer, University of Windsor, Capacitor Banks in Power Grids [email protected] Maher Abdelkhalek, Ahmed Awad, Ahmed Azab Abdelrahman Amer, Parallel Session 5: Mohammad Optimal Location and Sizing of Wind-based Location-inventory modeling Abdelrahman Borooshan, Mahzan Distributed Generators: Goodness of Fit for and methods 30 Amer Dalawir, Electric Vehicle Charging and Wind Speed University of Windsor, Ahmed Azab, [email protected] Profiles Session Chairs: Dr.Victor Shi Ahmed Awad, Time: 3:20 pm - 5:50 pm Maher Abdelkhalek Libin Guo Place: CEI 2102 Libin Guo, Beijing University of Modeling the Container Relocation Problem 47 Jian Li, Chemical Technology, with Truck Waiting Area in Terminal Yards University of Windsor, Guoqing Zhang [email protected] Victor Shi Jiangtao Hong, Optimization Model for Strategic 69 Wilfrid Laurier University, Victor Shi, Production and Distribution Planning of [email protected] Yibin Zhang Innovative Products

Tatsushi Nishi Ziang Liu, An Evolutionary Game Model in Closed- 21 Osaka University, Tatsushi Nishi Loop Supply Chain Parallel Session 6: [email protected] Green logistics and supply Yuyu Chen chain management 1 Nanjing University of Yuyu Chen, Decision Analysis Between Government 40 Aeronautics and Guoqing Zhang, and Competing Enterprises under E-waste Astronautics, Bangyi Li Take-back Regulations Session Chair: Dr. Tatsushi University of Windsor, [email protected] Nishi Tatsushi Nishi, An Efficient Heuristic Approach for Time: 3:20 pm - 5:50 pm Tatsushi Nishi Shuhei Akiyama, 27 Dynamic Multi-Commodity Network Place: CEI 2103 Osaka University, Raka Jovanovic, [email protected] Design Problem Stefan Voss

Sunday, July 28 Paper ID Speaker Author Paper Title Mingyue Jiang Cooperative Distribution VRP With Yirui, Deng, Parallel Session 7: 38 China University of Forward and Reverse Logistics Considered Petroleum, Mingyue Jiang Demand Concurrency Green logistics and supply [email protected] chain management 2 Ginger Ke Ginger Ke, Emergency Management for Offsite 41 Memorial University of Jiahong Zhao Hazardous Wastes: A Bilevel Approach Session Chairs: Dr. Ginger Ke Newfoundland, [email protected] Time: 1:30 pm - 3:00 pm Xueqing Guo Pricing Decisions In Dual-channel Closed- Chunfa Li, Place: CEI 2101 19 Tianjin University of loop Supply Chain Under Retailer's Risk Technology, Xueqing Guo Aversion And Fairness Preferences [email protected]

Ziru Lin A Penalty Mechanism Robust Model for Xiaofeng Xu, Parallel Session 8: 37 China University of MDVRP with Limited Supply in Refined Petroleum, Ziru Lin Oil Distribution Energy logistics and supply [email protected] chain Chenglong Wang Research on Refined Oil Distribution Chenglong Wang, Strategy 39 China University of Session Chairs: Dr. Saeideh Petroleum, Xiaofeng Xu and Oil Gas Recovery Joint Optimization [email protected] Salimpour Based on Environmental Protection Limit Saeideh Salimpour, Time: 1:30 pm - 3:00 pm Sophie-Charlotte Place: CEI 2102 Saeideh Salimpour Viaux, Ahmed A Clustering-Sequencing Approach for the 51 University of Windsor, Azab, Facility Layout Problem [email protected] Mohammed Fazle Baki

Bo Hu Study on Strategic Transition of E- Parallel Session 9: China University of Bo Hu commerce companies Based on Capability Petroleum, 56 Reconfiguration E-commerce and three-part [email protected] logistics Yuxin Tian Improve Bass Model's Predictive Power Chuan Zhang, Northeastern University, Through Online Reviews, Search Traffic [email protected] Yuxin Tian Session Chairs: Dr. Chuan 59 and Macroeconomic Data om Zhang Fawzat Alawneh Fawzat Alawneh, Global Warehouse with Cross-border Time: 1:30 pm - 3:00 pm 73 University of Windsor Gouqing Zhang Supply Chain Place: CEI 2103 [email protected]

Sunday, July 28 Paper ID Speaker Author Paper Title Bowen Zhang Bowen Zhang, Rebalancing Problem for Shared 36 Beijing University of Chemical Technology, Xiang Li Transportation in City’s Network [email protected] Peiyu Zhang, Guoqing Yang A Bi-objective Model for Last Mile Relief Parallel Session 10: Yankui Liu, 48 Hebei University, Network Design Problem under Uncertain Loblaw Session University of Windsor, Guoqing Yang, Demand [email protected] Guoqing Zhang Session Chairs: Dr. Guoqing Satyaveer S. Julio Montecinos, Satyaveer S. Yang Chuhan Understanding the Impact Cooperation of 57 Chuhan, Time: 3:20 pm - 5:50 pm Concordia University, Service Providers on the Last Mile Delivery satyaveer.chauhan@concordi Mustapha Place: CEI 2101 a.ca Ouhimmou Yuvraj Gajpal, Yuvraj Gajpal Electric Vehicle Routing Problem for 72 Srimantoorao University of Manitoba, Garbage Collection [email protected] Appadoo

Kin Keung Lai Yelin Fu, Early or Late? Timing-of-entry in a Dual- 28 Parallel Session 11: Shaanxi Normal University, Kin Keung Lai channel Supply Chain [email protected] Multiple- and omni-channel Hai Shen Hai Shen, supply Revenue-sharing Versus Wholesale Price 49 Xi’an International Studies Jun Hou, Session Chairs: Dr. Kin Keung University, Contracts under Chain-to-chain Competition Jie Liu Lai [email protected] Time: 3:20 pm - 5:50 pm Elkafi Hassini Srinivas Tamvada, Models and Hybrid Algorithms for Large 62 Bahareh Mansouri, Scale Less-than-truckload Freight Network Place: CEI 2102 McMaster University, [email protected] Elkafi Hassini Optimization

Hossein Beheshti Elkafi Hassini A Collaboration Platform for Freight 63 Fakher, Parallel Session 12: McMaster University, Routing Smart warehouse and [email protected] Elkafi Hassini inventory management Ben A. Chaouch Optimal Order Quantities for an Inventory 68 University of Windsor, Ben A. Chaouch System with Returns Depending on Earlier [email protected] Sales Session Chairs: Dr. Ben A. The Preference of VMI Contract on Mohammed Mohammed Chaouch Traditional RMI System in an Optimal 70 Almanaseer Almanaseer, Time: 3:20 pm - 5:50 pm Healthcare Supply Network: A Comparative University of Windsor, Guoqing Zhang Place: CEI 2103 [email protected] Study