American Institute of Mathematical Sciences

Advanced
  • Previous Article
    A bilinear relaxation based algorithm for concave piecewise linear network flow problems
  • JIMO Home
  • This Issue
  • Next Article
    Taking market forces into account in the design of production-distribution networks: A positioning by anticipation approach
January  2007, 3(1): 51-69. doi: 10.3934/jimo.2007.3.51

Logistics network design with supplier consolidation hubs and multiple shipment options

Michelle L.F. Cheong 1, , Rohit Bhatnagar 1, and  Stephen C. Graves 1,

1. 

Singapore-MIT Alliance, Nanyang Technological University, Singapore, Singapore, Singapore

Received  September 2005 Revised  August 2006 Published  January 2007

An important service provided by third-party logistics (3PL) firms is to manage the inbound logistics of raw materials and components from multiple suppliers to several manufacturing plants. A key challenge for these 3PL firms is to determine how to coordinate and consolidate the transportation flow, so as to get the best overall logistics performance. One tactic is to establish consolidation hubs that collect shipments from several suppliers, consolidate these shipments, and direct the consolidated shipments to the appropriate manufacturing plant. We consider the network design problem to implement this tactic, namely deciding the number, location and operation of consolidation hubs so as to minimize the total logistics costs for the network. To solve this network design problem, we define candidate shipping options for each potential hub, for which we can pre-compute the shipping quantities required from each supplier, and the incurred shipping costs and inventory holding costs. We formulate the problem as an integer linear optimization model and illustrate how to solve large instances using Lagrangian relaxation and a subgradient optimization algorithm. Our results indicate that the bounds obtained are fairly tight and are superior to the bounds obtained from the solution of the LP relaxation.
Keywords: supply chain design, inventory control., Hub location.
Mathematics Subject Classification: Primary: 90C5.
Citation: Michelle L.F. Cheong, Rohit Bhatnagar, Stephen C. Graves. Logistics network design with supplier consolidation hubs and multiple shipment options. Journal of Industrial & Management Optimization, 2007, 3 (1) : 51-69. doi: 10.3934/jimo.2007.3.51
[1]

Yeong-Cheng Liou, Siegfried Schaible, Jen-Chih Yao. Supply chain inventory management via a Stackelberg equilibrium. Journal of Industrial & Management Optimization, 2006, 2 (1) : 81-94. doi: 10.3934/jimo.2006.2.81
[2]

Feimin Zhong, Wei Zeng, Zhongbao Zhou. Mechanism design in a supply chain with ambiguity in private information. Journal of Industrial & Management Optimization, 2020, 16 (1) : 261-287. doi: 10.3934/jimo.2018151
[3]

Sanjoy Kumar Paul, Ruhul Sarker, Daryl Essam. Managing risk and disruption in production-inventory and supply chain systems: A review. Journal of Industrial & Management Optimization, 2016, 12 (3) : 1009-1029. doi: 10.3934/jimo.2016.12.1009
[4]

Jonas C. P. Yu, H. M. Wee, K. J. Wang. Supply chain partnership for Three-Echelon deteriorating inventory model. Journal of Industrial & Management Optimization, 2008, 4 (4) : 827-842. doi: 10.3934/jimo.2008.4.827
[5]

Ashkan Mohsenzadeh Ledari, Alireza Arshadi Khamseh, Mohammad Mohammadi. A three echelon revenue oriented green supply chain network design. Numerical Algebra, Control & Optimization, 2018, 8 (2) : 157-168. doi: 10.3934/naco.2018009
[6]

Zuo-Jun max Shen. Integrated supply chain design models: a survey and future research directions. Journal of Industrial & Management Optimization, 2007, 3 (1) : 1-27. doi: 10.3934/jimo.2007.3.1
[7]

Maryam Esmaeili, Samane Sedehzade. Designing a hub location and pricing network in a competitive environment. Journal of Industrial & Management Optimization, 2020, 16 (2) : 653-667. doi: 10.3934/jimo.2018172
[8]

Anh Son Ta, Le Thi Hoai An, Djamel Khadraoui, Pham Dinh Tao. Solving Partitioning-Hub Location-Routing Problem using DCA. Journal of Industrial & Management Optimization, 2012, 8 (1) : 87-102. doi: 10.3934/jimo.2012.8.87
[9]

Ali Naimi Sadigh, S. Kamal Chaharsooghi, Majid Sheikhmohammady. A game theoretic approach to coordination of pricing, advertising, and inventory decisions in a competitive supply chain. Journal of Industrial & Management Optimization, 2016, 12 (1) : 337-355. doi: 10.3934/jimo.2016.12.337
[10]

Jing Shi, Tiaojun Xiao. Service investment and consumer returns policy in a vendor-managed inventory supply chain. Journal of Industrial & Management Optimization, 2015, 11 (2) : 439-459. doi: 10.3934/jimo.2015.11.439
[11]

Ata Allah Taleizadeh, Leopoldo Eduardo Cárdenas-Barrón, Roya Sohani. Coordinating the supplier-retailer supply chain under noise effect with bundling and inventory strategies. Journal of Industrial & Management Optimization, 2019, 15 (4) : 1701-1727. doi: 10.3934/jimo.2018118
[12]

Prasenjit Pramanik, Sarama Malik Das, Manas Kumar Maiti. Note on : Supply chain inventory model for deteriorating items with maximum lifetime and partial trade credit to credit risk customers. Journal of Industrial & Management Optimization, 2019, 15 (3) : 1289-1315. doi: 10.3934/jimo.2018096
[13]

Kun-Jen Chung, Pin-Shou Ting. The inventory model under supplier's partial trade credit policy in a supply chain system. Journal of Industrial & Management Optimization, 2015, 11 (4) : 1175-1183. doi: 10.3934/jimo.2015.11.1175
[14]

Katherinne Salas Navarro, Jaime Acevedo Chedid, Whady F. Florez, Holman Ospina Mateus, Leopoldo Eduardo Cárdenas-Barrón, Shib Sankar Sana. A collaborative EPQ inventory model for a three-echelon supply chain with multiple products considering the effect of marketing effort on demand. Journal of Industrial & Management Optimization, 2020, 16 (4) : 1613-1633. doi: 10.3934/jimo.2019020
[15]

Xia Zhao, Jianping Dou. Bi-objective integrated supply chain design with transportation choices: A multi-objective particle swarm optimization. Journal of Industrial & Management Optimization, 2019, 15 (3) : 1263-1288. doi: 10.3934/jimo.2018095
[16]

Reza Lotfi, Yahia Zare Mehrjerdi, Mir Saman Pishvaee, Ahmad Sadeghieh, Gerhard-Wilhelm Weber. A robust optimization model for sustainable and resilient closed-loop supply chain network design considering conditional value at risk. Numerical Algebra, Control & Optimization, 2020  doi: 10.3934/naco.2020023
[17]

Hamid Norouzi Nav, Mohammad Reza Jahed Motlagh, Ahmad Makui. Modeling and analyzing the chaotic behavior in supply chain networks: a control theoretic approach. Journal of Industrial & Management Optimization, 2018, 14 (3) : 1123-1141. doi: 10.3934/jimo.2018002
[18]

Azam Moradi, Jafar Razmi, Reza Babazadeh, Ali Sabbaghnia. An integrated Principal Component Analysis and multi-objective mathematical programming approach to agile supply chain network design under uncertainty. Journal of Industrial & Management Optimization, 2019, 15 (2) : 855-879. doi: 10.3934/jimo.2018074
[19]

K. F. Cedric Yiu, S. Y. Wang, K. L. Mak. Optimal portfolios under a value-at-risk constraint with applications to inventory control in supply chains. Journal of Industrial & Management Optimization, 2008, 4 (1) : 81-94. doi: 10.3934/jimo.2008.4.81
[20]

Dandan Hu, Zhi-Wei Liu. Location and capacity design of congested intermediate facilities in networks. Journal of Industrial & Management Optimization, 2016, 12 (2) : 449-470. doi: 10.3934/jimo.2016.12.449

2019 Impact Factor: 1.366

Tools

Metrics

  • PDF downloads (89)
  • HTML views (0)
  • Cited by (24)

Other articles
by authors

[Back to Top]

Copyright © 2020 American Institute of Mathematical Sciences