Supply Chain Management Logistics AND INNOVATIVE STRATEGIES AND PRACTICAL SOLUTIONS © 2016 by Taylor & Francis Group, LLC INDUSTRIAL AND SYSTEMS ENGINEERING SERIES Series Editor Waldemar Karwowski PUBLISHED TITLES: Supply Chain Management and Logistics: Innovative Strategies and Practical Solutions Zhe Liang, Wanpracha Art Chaovalitwongse, and Leyuan Shi Mobile Electronic Commerce: Foundations, Development, and Applications June Wei Managing Professional Service Delivery: 9 Rules for Success Barry Mundt, Francis J. Smith, and Stephen D. Egan Jr. Laser and Photonic Systems: Design and Integration Shimon Y. Nof, Andrew M. Weiner, and Gary J. Cheng Design and Construction of an RFID-enabled Infrastructure: The Next Avatar of the Internet Nagabhushana Prabhu Cultural Factors in Systems Design: Decision Making and Action Robert W. Proctor, Shimon Y. 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Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for identification and explanation without intent to infringe. Visit the Taylor & Francis Web site at http://www.taylorandfrancis.com and the CRC Press Web site at http://www.crcpress.com Contents List of Figures .......................................................................................................vii List of Tables ...........................................................................................................xi Preface ...................................................................................................................xiii Editors ..................................................................................................................xvii Contributors .........................................................................................................xix Section I Supply Chain Strategy and Coordination 1. Supply Chain Frameworks: A Constant in the Midst of Change .........3 Tan Miller 2. Future Research on Multiobjective Coordinated Scheduling Problems for Discrete Manufacturing Enterprises in Supply Chain Environments ....................................................................................19 Jun Pei, Xinbao Liu, Wenjuan Fan, Athanasios Migdalas, and Panos M. Pardalos Section II Supply Chain Network Optimization 3. Integrated Production/Distribution/Routing Planning for Supply Chain Networks: A Review ...................................................43 Lei Lei, Rosa Oppenheim, Lian Qi, Hui Dong, Kangbok Lee, and Shengbin Wang 4. Increasing the Resiliency of Local Supply Chain Distribution Networks against Multiple Hazards ........................................................87 Sarah G. Nurre, Thomas C. Sharkey, and John E. Mitchell 5. Nested Partitions for Large-Scale Optimization in Supply Chain Management ....................................................................................123 Weiwei Chen and Leyuan Shi Section III Inventory Management in the Supply Chain 6. A Schedule-Based Formulation for the Cyclic Inventory Routing Problem .........................................................................................153 Zhe Liang, Rujing Liu, and Wanpracha Art Chaovalitwongse v © 2016 by Taylor & Francis Group, LLC vi Contents 7. An Application of an Inventory Model for Production Planning ....179 Paveena Chaovalitwongse, Pakpoom Rungchawalnon, and Kwankeaw Meesuptaweekoon Section IV Financial Decisions in the Supply Chain 8. A Game of Competitive Investment: Overcapacity and Underlearning .....................................................................................197 Jian Yang, Yusen Xia, and Junmin Shi 9. A Multiperiod Multiclass High-Speed Rail Passenger Revenue Management Problem ................................................................................231 Ying Qin, Zhe Liang, Wanpracha Art Chaovalitwongse, and Shaozhong Xi Index .....................................................................................................................257 © 2016 by Taylor & Francis Group, LLC List of Figures Figure 1.1 Hierarchical supply chain planning framework ..........................5 Figure 1.2 Hierarchical warehouse planning ..................................................7 Figure 1.3 F ramework of how warehousing decisions fit into a planning hierarchy............................................................................7 Figure 1.4 A hierarchical framework for inventory management..............10 Figure 1.5 A hierarchical supply chain performance measurement framework ........................................................................................13 Figure 1.6 I llustrative hierarchical performance measures for the distribution function ......................................................................14 Figure 3.1 Network structure and material flow ..........................................48 Figure 3.2 An overview of existing procedures for solving the integrated problem .........................................................................78 Figure 3.3 A general procedure to define and solve modern supply chain operations problems with a simulation framework........82 Figure 4.1 Locations of Stewart’s Shops stores ..............................................88 Figure 4.2 Heat map displaying the 330 Stewart’s Shops stores and their respective total demand level, where darker shading indicates a higher level of demand ..............................................96 Figure 4.3 Single hazard computational results ...........................................98 Figure 4.4 H urricane hazard solutions. (a) 17 generators, (b) 33 generators, and (c) 50 generators ........................................99 Figure 4.5 Flood hazard solutions. (a) 17 generators, (b) 33 generators, and (c) 50 generators .....................................................................100 Figure 4.6 Blizzard hazard solutions. (a) 17 generators, (b) 33 generators, and (c) 50 generators ......................................100 Figure 4.7 Ice storm hazard solutions. (a) 17 generators, (b) 33 generators, and (c) 50 generators ......................................101 Figure 4.8 All hazards computational results .............................................102 Figure 4.9 S olutions for all hazards with equal sampling. (a) 17 generators, (b) 33 generators, and (c) 50 generators .......102 vii © 2016 by Taylor & Francis Group, LLC viii List of Figures Figure 4.10 S olutions for all hazards with hazard-based sampling. (a) 17 generators, (b) 33 generators, and (c) 50 generators......103 Figure 4.11 O ptimality gaps when the converged solution to the top row hazard is evaluated under the scenarios and optimal solution to the hazard described in the first column ..........................................................................................105 Figure 4.12 P ercentage of matching solutions using the count metric. ...106 Figure 4.13 H eat map corresponding to the values shown in Figure 4.12 where darker represents closer to 1. ....................107 Figure 4.14 O ptimality gaps capturing the interdependence on external services and interchangeability of different objectives ......................................................................................109 Figure 4.15 Heat map displaying the 330 Stewart’s Shops stores and their respective count of instances where they are selected to receive a generator. A darker color indicates a higher count .................................................................................110 Figure 4.16 P otential starting and ending points for hurricane, blizzard, and ice storm tracks ...................................................112 Figure 5.1 IHLP: a partial sample. .................................................................137 Figure 5.2 IHLP: a complete sample solution ..............................................138 Figure 6.1 I nventory flow network containing four periods for a customer. The maximum inventory capacity of the customer is 4, and the demands are 2, 1, 2, and 3 for period 1, 2, 3, and 4, respectively. The vehicle capacity is 3. (a) Inventory flow network for ML policy. (b) Inventory flow network for OU policy .........................................................163 Figure 6.2 I nventory flow network for a three-period inventory routing problem. The initial inventory level is 2. The maximum inventory capacity of the customer is 4, and the demands are 2, 1, and 2 for period 1, 2, and 3, respectively. The vehicle capacity is 3. (a) Inventory flow network for ML policy. (b) Inventory flow network for OU policy. .................................................................................172 Figure 7.1 A finishing process of rolled tissues ..........................................180 Figure 7.2 Overview of current production planning process .................184 Figure 7.3 Production planning performance indicators ..........................184 Figure 7.4 Overview of the proposed production planning process .......186 © 2016 by Taylor & Francis Group, LLC List of Figures ix Figure 7.5 Components of the proposed planning method ......................187 Figure 7.6 Computational results for production planning ......................190 Figure 7.7 Computational results for raw materials ...................................191 Figure 8.1 Iso-valued curves A = 27/4 .........................................................216 n Figure 8.2 Iso-valued curves C = 0...............................................................217 n Figure 9.1 Beijing–Shanghai high-speed railway. .......................................235 Figure 9.2 Ticket price of Beijing–Shanghai high-speed railway. .............236 Figure 9.3 An example containing three trips between three cities ........238 Figure 9.4 Demand flow balance between variables ..................................240 Figure 9.5 Demand over time ........................................................................248 © 2016 by Taylor & Francis Group, LLC © 2016 by Taylor & Francis Group, LLC