2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
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2 - An Endogenous Structural Credit Risk Model And Its Application
In Pricing Derivatives With Credit Risk
Huawei Niu, Nanjing Audit University, School of Finance, Nanjing,
211815, China, Yajuan Lu
We propose an endogenous structural credit risk model with rollover debt by
incorporating with the optimal contracting between the agent and equity holders.
The model quantitatively shows that the agency costs induced by the moral
hazard can endogenously have significant impacts on a firm’s credit risk. Besides,
we embed this structural approach into pricing vulnerable options as an
application.
3 - Approximation Of Long Memory Process With Short Memory
Process With Application To Option Valuation
Barret Pengyuan Shao, Crabel Capital Management,
Charlottesville, VA, Contact:
Options on an asset which follow a long memory process are difficult to value,
due to the existence of arbitrage opportunities. Here we show how to avoid the
problem of arbitrage opportunities and value vanilla European options when
underlying asset returns follow a FARIMA processes which is widely used as an
model of long memory price processes. By approximating FARIMA by a station-
ary ARMA process, we show that the well understood option values for a suffi-
ciently close stationary ARMA process can be taken as option values for the
FARIMA process, with very low probability of error. We examine how long
memory affects the option values and implied volatility surface.
WA59
Cumberland 1- Omni
Sharing Logistics
Sponsored: TSL, Facility Logistics
Sponsored Session
Chair: Wei Qi, Lawrence Berkeley National Laboratory, 1 Cyclotron Rd,
Berkeley, CA, 94720, United States,
1 - A Study Of Corporate Barter Exchange Mechanisms
Min Zhao, University of California at Berkeley, Berkeley, CA,
United States, , Zuo-Jun Max Shen,
Xiaobo Zhao
The study considers a modern corporate barter platform operating under different
exchange mechanisms. It focuses on the chance that a participant can find
exchange partners and his waiting time before being able to exchange. We derive
closed form waiting time distribution under certain conditions and analyze
participant’s preference according to the waiting time. Insights on improving the
performance of a barter platform are also provided.
2 - Household-level Economies Of Scale In Transportation
John Gunnar Carlsson, University of Southern California,
One of the fundamental concerns in the analysis of logistical systems is the trade-
off between localized, independent provision of goods and services versus
provision along a centralized infrastructure such as a backbone network. We
study the “mini-economies” of scale that arise when households make multi-stop
trips rather than using package delivery services. Our study is facilitated by an
analysis of the Generalized Travelling Salesman Problem in the Euclidean plane.
3 - Shared Mobility For Last-mile Delivery: Implications Of Costs And
Green House Emissions
Wei Qi, Lawrence Berkeley National Laboratory,
, Lefei Li, Sheng Liu, Zuo-Jun Max Shen
We evaluate the prospect where shared mobility of passenger cars prevails
throughout urban areas for home delivery services. We develop logistics planning
models that characterize drivers’ responses to wages, optimal open-loop routes
and service zone design. Then we prescribe several scenarios where this business
model is economically and environmentally favorable.
4 - Setting Inventory Levels In A Bike Sharing Network
Michal Tzur, Professor, Tel Aviv University, Tel Aviv, Israel,
Sharon Datner, Tal Raviv
Bike sharing operators address the non-homogeneous asymmetric demand
processes by repositioning operations. This is a challenging task due to the nature
of the user behavior that creates interactions among inventory levels at different
stations. For example, an empty/full station can create a spill-over of demand to
nearby stations. For the first time, we take this effect into consideration when
setting target inventory levels for repositioning. We develop a robust guided local
search algorithm and show that neglecting the interactions among stations leads
to inferior decision-making.
WA60
Cumberland 2- Omni
Understanding and Optimizing Route and Mode
Choices in a Dynamic/Multimodal Environment
Sponsored: TSL, Urban Transportation
Sponsored Session
Chair: Monireh Mahmoudi, Arizona State University, Arizona State
University, Tempe, AZ, 85281, United States,
1 - A Dynamic Programming Approach Based On State Space Time
Network Representations For The Pickup And Delivery Problem
Monireh Mahmoudi, PhD Student, Arizona State University,
Tempe, AZ, 85281, United States, ,
Xuesong Zhou
This research proposes a new time-discretized multi-commodity network flow
model for the VRPPDTW based on the integration of vehicles’ carrying states
within space-time transportation networks. Our three-dimensional state-space-
time network construct is able to comprehensively enumerate possible
transportation states at any given time along vehicle space-time paths, and
further allows a forward dynamic programming solution algorithm to solve the
single-VRPPDTW. By utilizing a Lagrangian relaxation approach, the primal
multi-VRP is decomposed to a sequence of single-vehicle routing sub-problems,
with Lagrangian multipliers for individual passengers’ requests.
2 - Route Choice In Highly Disrupted Network: Learning, Inertia And
Real-time Information
Xinlian Yu, University of Massachusetts, Amherst, MA,
United States, Song Gao
This paper studies the role of inertia, learning and real-time information in route-
choice decisions in highly disrupted networks where travel time varies greatly
with significant delays. A route-choice experiment with two different scenarios
was conducted: the Information scenario provides subjects with real-time
information regarding a probable incident and the Incident scenario does not. In
both scenarios, subjects were provided with feedback information about the
actual travel times on the chosen route. A discrete choice model with a Mixed
Logit specification, accounting for panel effects, was estimated based on the
experiment’s data.
3 - Understanding Traveler Route Choices In Stochastic Multimodal
Travel Environment Using Automatic Fare Collection Data
Laiyun Wu, University at Buffalo, 326 Bell Hall, University at
Buffalo, Buffalo, NY, 14226, United States, ,
Jee Eun Kang, Alexander Nikolaev
The goal of this paper is to extract traveler behavior patterns from route choice
observations in a stochastic multimodal environment, based on Automatic Fare
Collection (AFC) data. First, we reconstruct the stochastic travel environment to
enable simulation, with the travel times, transfer times, and level-of-service
information accounted for. Second, route choices are analyzed to understand and
model traveler decision-making.
4 - Personalized Multimodal Mobility Options Discovery In
A Social Structure
Ali Arian, PhD Student, University of Arizona, Tucson, AZ, 85721,
United States, , Yi-Chang Chiu
This study uses a supernetwork to investigate the feasibility and attractiveness of
multimodal mobility options. The modeling approach considers driving, walking,
public transit and carpooling among users in an existing social structure. Besides
desirability measures, algorithmic details and case studies using Metropia data are
presented.
WA61
Cumberland 3- Omni
Shared-use Rail Corridor Operation and Planning
Sponsored: Railway Applications
Sponsored Session
Chair: Bo Zou, University of Illinois at Chicago, 2073 ERF, 842 West
Taylor Street, Chicago, IL, 60607, United States,
1 - Capacity Screening Tool For Mixed Operations
Mei-Cheng Shih, University of Illinois at Urbana - Champaign,
Urbana, IL, 61801,
In order to determine the appropriate solutions for rail network congestion, we
need to identify the capacity constraints of the network first. In this study, we will
develop a capacity screening tool based on the concept of “Root Cause Analysis”
proposed by White (2005). This tool can calculate the traffic conflict density by
taking account the current train schedule and the associated train departure and
trip time variation. The traffic conflict density can later be used to identify the
capacity constraints of a mainline. Using this tool can help the practitioners to
find the weakness of their network in the most efficient way.
WA61