Informs 2015

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INFORMS Philadelphia – 2015
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5 - Facility Location Problem Considering Time Window and Land
use Plan using GIS
Eunsu Lee, Assistant Professor, New Jersey City University, 2039
John F. Kennedy Blvd, Jersey City, NJ, 07305, United States of
America, Sumadhur Shakya, Alan Dybing
This paper investigates the facility location problem through network space,
considering traversable truck roads, thereby providing a strategic decision for
identifying a depot location in consideration of vehicle routings from a real
application. This study provides a ready-to-use example of how to adopt state-of-
the-art spatial technology and operations research using Geographic Information
Systems (GIS), and bring it to state-of-practice.
SA69
69-Room 201C, CC
Facility Location and Inventory Routing
Sponsor: Transportation, Science and Logistics
Sponsored Session
Chair: Natashia Boland, Georgia Institute of Technology, 755 Ferst
Drive, NW, Atlanta, GA, 30332-0205, United States of America,
1 - Facility Location Design under Continuous Traffic Equilibrium
Zhaodong Wang, University of Illinois, 205 N. Mathews Ave,
Urbana, IL, United States of America
Yanfeng Ouyang
This paper proposes both a continuum approximation model and a discrete
mixed-integer program model to solve the facility location problem under traffic
congestion in continuous space. Customized algorithms are developed and
analytical properties are presented. Numerical examples show the advantages of
the continuous models and shed managerial insights.
2 - Winter is Coming: A Robust Optimization Approach to
Inventory Routing
Joel Tay, Graduate Student, Operations Research Center, MIT, 77
Massachusetts Ave, Bldg. E40-149, Cambridge, MA, 02139,
United States of America, , Swati Gupta,
Dimitris Bertsimas
We consider the finite horizon inventory routing problem with uncertain
demand, e.g. supplying residential heating oil to customers. Current techniques
that solve this problem with stochastic demand do not scale to real-world data
sizes. We propose a MIP formulation using robust optimization that is made
tractable with heuristic route selection, warm starts and column generation. We
show promising computational results that demonstrate scalability to real-world
applications.
3 - A Matheuristic for the Multi-vehicle Inventory Routing Problem
Natashia Boland, Georgia Institute of Technology, 755 Ferst Drive,
NW, Atlanta, GA, 30332-0205, United States of America,
, Cristina Archer,
Grazia Speranza
We consider the inventory routing problem in which a supplier must replenish a
set of customers using a limited fleet of capacitated vehicles over a discrete time
horizon. The goal is to minimize the total cost of the distribution, comprising the
inventory costs at supplier and customers, and the routing cost. We present a
matheuristic, combining tabu search and integer programming formulations.
Extensive computational experiments on benchmark instances show the
effectiveness of the method.
SA70
70-Room 202A, CC
Railway Applications Section Student Paper Award
Sponsor: Railway Applications
Sponsored Session
Chair: April Kuo, BNSF Railway, 2400 Western Center Blvd.,
Fort Worth, TX, United States of America,
1 - Railway Applications Student Paper Award
April Kuo, BNSF Railway, 2400 Western Center Blvd., Fort
Worth, TX, United States of America,
Rail Applications Section (RAS) sponsored a student research paper contest on
analytics and decision making in railway applications. Papers must advance the
application or theory of OR/MS for improvement of freight or passenger railway
transportation, and it must represent original research that has not been
published elsewhere by the time it is submitted. Authors of the First, Second and
Third Place award winning papers will present their papers in this session.
SA71
71-Room 202B, CC
Transportation Network Analysis and Optimization
Sponsor: TSL/Urban Transportation
Sponsored Session
Chair: Andres Medaglia, Professor, Universidad de los Andes, Cra 1 Este
No 19A - 40, Bogota, Colombia,
1 - On the Robust Shortest Path Problem:
A Pulse Algorithm Approach
Daniel Duque, Instructor, Universidad de los Andes, Cr 1E N 19A-
40, Bogota, Colombia,
Andres Medaglia
In this variant of the robust shortest path problem, the cost of traversing an arc is
given by a discrete set of scenarios. The problem is then to find a (robust) path
that takes into account the information arising from the multiple cost realizations
of the possible scenarios. To account for a robust path, we adopt the bw-
robustness criterion, which ameliorates the dramatic role played by the worst case
analysis. To solve the problem, we extend the pulse algorithm, a general-purpose
solution strategy that has been used on shortest path problems with side
constraints. The proposed algorithm compares favorably against an integer
programming approach both in terms of speed and scalability.
2 - Reliability of Interdependent Urban Infrastructure Network:
Failure Propagation and Consequential Social Impact
Liqun Lu, UIUC, United States of America, ,
Yanfeng Ouyang, Xin Wang
Modern city relies on a network of multiple interdependent infrastructure
systems, hence more vulnerable. Random or premeditated infrastructure
disruption can propagate to large areas and cause social disasters. The system
reliability is investigated under both deterministic and stochastic disruption
propagation and social impacts are evaluated by a user equilibrium model.
3 - Lagrangian Relaxation Solution Approach for the Vehicle Routing
Problem with Pickup and Delivery
Monirehalsadat Mahmoudi, Arizona State University, School of
Sustainable Engineering and the Built Environment, Tempe, AZ,
United States of America, , Xuesong Zhou
We propose a new time-discretized multi-commodity network flow model for the
pickup and delivery problem with time windows based on the integration of
vehicles’ carrying-states within space-time transportation networks. By a
Lagrangian relaxation approach, the primal multi-vehicle routing problem is
decomposed to a sequence of single vehicle routing sub-problems with
Lagrangian multipliers for individual passengers’ request, each can be solved by a
forward dynamic programming solution algorithm.
4 - Combined Maintenance-routing Optimization: The Case of a
Water Utility
Andres Medaglia, Professor, Universidad de los Andes, Cra 1 Este
No 19A - 40, Bogota, Colombia, ,
Daniel Duque, Raha Akhavan-Tabatabaei, John E. Fontecha,
Juan Pablo Rodriguez
The combined maintenance-routing optimization problem deals with planning
and scheduling maintenance operations for a set of geographically-distributed
sites that are subject to non-deterministic failures. To solve this problem, a
maintenance model determines the optimal time to perform preventive
maintenance operations for each site; while a routing optimization engine
schedules visits of a set of technicians that perform the operations. We present a
case study in the city of Bogot·, where the water utility needs to perform
maintenance operations to prevent sediment-related blockages of the sewer
system.
SA69