3 Presentations

• 
  01:00 PM - 01:22 PM

  Large-scale Multi-modal Transit Line Planning via Flow Relaxations

  • Ning Duan, presenter, Cornell University
  • Oktay Gunluk, Georgia Institute of Technology
  • Samitha Samaranayake, Cornell University

  As mobility-on-demand services revolutionize urban transportation by providing convenient traveling choices to the general population, they also motivate the re-design of traditional transit service to better integrate with a multi-modal environment. Recent modeling attempts include using heuristics or data-driven approaches to handle the problem. However, there has been limited work on general optimization frameworks for planning the multimodal transportation system in a systematic and tractable manner.

  We study the problem of designing efficient transit line routes and frequencies to serve demand given the availability of complementary first- and last-mile on-demand services in the network. We formulate a mixed integer optimization program to select the optimal lines given an available candidate set of options. Later, we relax the assumption and design column generation algorithms to come up with the candidate set of lines. We demonstrate the efficiency of our approach on stimulating ridership with limited budget with real travel data from metropolitan cities.

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  01:22 PM - 01:44 PM

  Design and Optimization of a Home Appliance Closed-loop Supply Chain Network with Quantity Discount Under Uncertainty

  • Saman Hassanzadeh Amin, presenter, Toronto Metropolitan University
  • Shahab Rahiminia , Toronto Metropolitan University
  • Liping Fang, Toronto Metropolitan University

  There are both forward and reverse supply chains in a closed-loop supply chain. In this talk, design and optimization of a home appliance closed-loop supply chain network is discussed. The proposed optimization model includes three objective functions. Quantity discount and uncertainty in some parameters of the model are considered. The application of the proposed optimization model is discussed in Ontario, Canada. In addition, the sensitivity analyses and managerial insights are reviewed. The results show that the proposed optimization model can handle quantity discount and uncertainty during the network optimization.

• 
  01:44 PM - 02:06 PM

  Optimization of a Home Appliance Closed-Loop Supply Chain Under Uncertainty

  • Jorge Restrepo Diaz, presenter, Toronto Metropolitan University
  • Saman Hassanzadeh Amin, Toronto Metropolitan University

  This study emphasizes the configuration of a Closed-Loop Supply Chain (CLSC) under uncertainty, focusing on metal waste related to home appliances and auto parts. This research addresses End-Of-Use (EOU), End-Of-Life (EOL), and commercial returns by integrating stochastic techniques with a multi-objective mixed-integer linear programming model to optimize facility selection and order allocation within a home appliance CLSC network. The proposed network employs new and recycled components to create new products. The proposed model intends to maximize the total profit while minimizing the environmental impacts. The model is solved using an augmented ε-constraint framework in two stages. This framework is applied to a microwave manufacturing network in Canada using real data on different transportation modes and distances from Google Maps. The results show the flows of products and parts and the facility selection within the network. This research concludes with a summary of key insights and recommendations.