2016 INFORMS Annual Meeting Program

WA61

INFORMS Nashville – 2016

WA60 Cumberland 2- Omni

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, niuhuawei@gmail.com, 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 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, Barret Pengyuan Shao, Crabel Capital Management, Charlottesville, VA, Contact: barretshao@gmail.com Min Zhao, University of California at Berkeley, Berkeley, CA, United States, vivianmzhao@berkeley.edu, 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, jcarlsso@usc.edu 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, qiwei@berkeley.edu, 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, tzur@eng.tau.ac.il, 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. Berkeley, CA, 94720, United States, qiwei@berkeley.edu 1 - A Study Of Corporate Barter Exchange Mechanisms

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, mmahmoudi@asu.edu 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, mmahmoudi@asu.edu, 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, xinlianyu@umass.edu, 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, laiyunwu@buffalo.edu, 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, arian@email.arizona.edu, 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, bzou@uic.edu 1 - Capacity Screening Tool For Mixed Operations Mei-Cheng Shih, University of Illinois at Urbana - Champaign, Urbana, IL, 61801, mshih2@illinois.edu 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.

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