2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
354
2 - Discovering Relationships Of Round-trip Carsharing Factors With
Association Rules Technique
Dahye Lee, Texas A&M University, College Station, TX,
United States, Luca Quadrifoglio,
Benedetta Sanjust di Teulada, Italo Meloni
The objective of this research is a comprehensive analysis for discovering
relationships between factors of round-trip carsharing with the association rules
approach. Results of analysis show that the strongest dependent variables do not
have high correlations with the variables of distance from customers’ residence
locations. Although the results gave an idea of connections of round-trip
operations characteristics, the degree of impact of each variable still need to be
investigated. The goal for future studies is to maximize connectivity to public
transportation to help in reducing congestion and pollution.
3 - Household Use Of Autonomous Vehicles: Modeling Framework
And Traveler Adaptation
Yashar Khayati, University at Buffalo, Amherst, NY, United States,
, Jee Eun Kang, Mark Henry Karwan,
Chase Murray
We define a framework to model and evaluate potential household-level use of
Autonomous Vehicles (AVs), to understand advantages, potential issues and
negative external effects. We introduce a new formulation, the Household
Activity Pattern Problem for AVs, to simulate the travel patterns of people using
AVs. The key modeling challenge is to include modeling capabilities of driverless
parking, pickup, drop-off and waiting during travelers’ engagement in activities.
We develop solution approaches to this NP-hard problem and conduct a scenario
analysis to evaluate changes in travel behavior.
TD61
Cumberland 3- Omni
Routing and Scheduling
Sponsored: TSL, Freight Transportation & Logistics
Sponsored Session
Chair: Ali Ekici, Ozyegin University, TBD, Istanbul, TBD, Turkey,
1 - Integration Of Passenger And Freight Rail Scheduling
Liang Liu, University of Southern California, Los Angeles, CA,
United States, Maged M Dessouky
We study the integration of passenger and freight rail scheduling to improve the
efficiency of freight trains while maintaining the punctuality of passenger trains.
An optimization model that jointly considers the travel times of freight trains and
the tardiness of the passenger trains is formulated. We proposed a decomposition
based solution procedure to solve the problem, in which optimization-based or
heuristic algorithms are applied on each of the subproblems.
3 - Congestion Reduction Through Efficient Empty
Container Movement
Santiago Carvajal, University of Southern California, 1150 W 29th
Street, Los Angeles, CA, 90007, United States,
The optimization problem for efficiently routing multi-container trucks to better
reposition both loaded and empty containers is studied. Our formulation adds the
multi-container truck to the empty container reuse problem. Our aim is that by
more efficiently routing trucks that the number of truck trips would be reduced,
thus decreasing transportation costs, and reducing the natural environmental
impact of transporting goods.
4 - A Tour Generation-based Algorithm For An Inventory
Routing Problem
Ali Ekici, Ozyegin University, Istanbul, Turkey,
, Okan Orsan Ozener
We study a variant of inventory routing problem and develop an integrated two-
phase solution approach. In the first phase, we cluster the customers such that
each clustered is served by a single vehicle. Then, in the second phase, we
determine the delivery routes and volumes for each cluster using an integer
programming based heuristic approach. In this phase, we first generate several
tours and solve mixed integer program to choose among these generated tours
and determine the delivery volumes. We compare the performance of the
proposed algorithm against the ones in the literature.
TD62
Cumberland 4- Omni
Data and Decisions for Airline and
Air Traffic Management
Sponsored: Aviation Applications
Sponsored Session
Chair: Alexandre Jacquillat, Massachusetts Institute of Technology,
77 Massachusetts Avenue, Cambridge, MA, 02116, United States,
1 - Flight Scheduling, Flight Planning And Operations Recovery To
Minimize Airline Operating Costs
Jane Lee, University of Illinois at Urbana Champaign,
The focus of this work is to evaluate impact of stochasticity of disruptions on
airline’s recovery decision. In particular, we aim to model the dynamic
recoverability of flight schedule in response to disruptions based on Stochastic
Queueing Model of airport congestion. We consider the typical mechanisms of
departure time holdings, flight cancellations, and aircraft swaps used in aircraft
recovery in practice today using Integer Programming. Additionally, we also
consider dynamic decision making in recovery based on Dynamic Programming
model. Our real-world experiments involve the original schedule of a major
carrier in the US and disruptions at a secondary hub.
2 - A Combinatorial Auction For Allocation Of Departure And
Arrival Slots
Alexander Estes, University of Maryland-College Park, College
Park, MD, 20742, United States, ,
Michael O Ball, Mark M Hansen, Yulin Liu
We present a combinatorial auction mechanism for the allocation of arrival and
departures slots at an airport. This mechanism selects a profile of slots that will be
available and provides an allocation of these slots to airlines based on their bids in
the auction. Vickrey-Clarke-Grove payments are used so that it dominant strategy
for airlines to bid truthfully. This provides a way in which the airlines’ valuation
of congestion costs can be incorporated into slot allocations.
3 - Data-driven Choice-based Airline Fleet Assignment
Chiwei Yan, Massachusetts Institute of Technology,
, Cynthia Barnhart, Vikrant Vaze
We propose models to incorporate customer choice behaviors into the capacity
allocation problem under a network revenue management setting, namely, the
airline fleet assignment problem. Unlike network revenue management, the
capacity allocation problem with customer choice is usually intractable for real-
world instances. We thus devise efficient decomposition approaches with provable
performance guarantees. Our approach is data-driven in nature, which learns a
choice model from transaction data and builds effective fleeting decisions based
on that.
4 - A Model For Airport Schedule Coordination Based On The
IATA Guidelines
Nuno Ribeiro, University of Coimbra, Coimbra, Portugal,
The International Air Transport Association (IATA) slot allocation process is the
dominant demand management mechanism used at busy airports worldwide. In
this process, each coordinated airport provides its “declared capacity”, the airlines
submit their scheduling requests, and a slot coordinator sets the schedule of
flights at the airports. This research develops a new modeling approach to support
slot coordinators to accommodate airline preferences better, while complying with
the IATA guidelines and other constraints. Results are shown from a case study at
Madeira airport (FNC).
TD61