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INFORMS Nashville – 2016

107

SD39

207A-MCC

Queueing Systems and Approximations

Sponsored: Applied Probability

Sponsored Session

Chair: John Hasenbein, University of Texas-Austin, Austin, TX,

United States,

jhas@mail.utexas.edu

1 - Optimal Routing To Remote Queues

Yunan Liu, NC State University, Raleigh, NC, United States,

yliu48@ncsu.edu,

Shucangchi He, Yao Yu

We develop optimal routing policies for remote queueing systems, in which each

arrival, after being routed to join one of several single-server queues in parallel,

will experience a pre-arrival delay. Motivated by service systems in which system

state (e.g., queue length and waiting time) is available for routing decisions, we

intend to use pre-arrival delays to model commute times of arrivals, such as

patients’ transportation times before arriving at clinics and data packets’

transmission times to web servers. In order to minimize the delay, we propose a

new state-dependent probabilistic routing policy.

2 - Complete Resource Pooling In Open Shop Networks

Shuangchi He, National University of Singapore, Singapore,

heshuangchi@nus.edu.sg

, Gideon Weiss, Hanqin Zhang

In an open shop network, each customer needs to go through all stations once,

but the order of visiting each station is irrelevant. Can this flexibility in service

order give us an edge in reducing customer waiting times? In this paper, we

consider an open shop network consisting of two stations. We find routing and

sequencing policies that are asymptotically optimal when the open shop network

is operated in heavy traffic. We prove that under the obtained scheduling policies,

customer waiting times in an open shop network are asymptotically close to the

waiting times in a GI/GI/2 queue with the same traffic intensity.

3 - Stein Method And Moderate Deviations For Steady-state

Diffusion Approximations

Jim Dai, Cornell University,

jd694@cornell.edu,

Fang Xiao

Service levels such as no more 5% of callers have to wait 3 minutes orlonger are

common performance measures for many service systems. Iwill use the Erlang-C

system to explain how Stein method can be used todevelop moderate deviations

bounds for steady-state diffusionapproximations of these performance measures.

This is the joint work with Xiao Fang at NUS and Chinese University of Hong

Kong.

4 - Optimal Service Rate And Admission Control For A Queue

Levent Kocaga, Yeshiva University,

kocaga@yu.edu

We study the joint service rate and admission control problem for a multi-server

service system modeled as a G/M/N+GI queue. We consider the infinite horizon

discounted cost criterion as well as the infinite horizon average cost criterion

where costs are associated with customer waiting, customer abandonment, and

service rate control. Instead of solving the potentially intractable original

queueing control problem, we solve an approximating diffusion control problem

(DCP) and show that the optimal control is of threshold and feedback type. We

utilize the solution to the DCP to construct a control policy for the original

queueing control problem.

SD40

207B-MCC

Supply Chain Mgt

Contributed Session

Chair: Xinghao Yan, Western University, London, ON, Canada,

xyan@ivey.uwo.ca

1 - Simulation And Optimization For Reevaluating Order Fulfillment

Plans In An Online Retail Environment

Amir Hossein Kalantari, University of Wisconsin Milwaukee,

Milwaukee, WI, United States,

kalanta2@uwm.edu

, Matthew

Petering

Online retailing has expanded dramatically in recent years and is expected to

continue growing in the future. Online retailers typically operate a number of

fulfillment centers that are located in different geographical regions. When an

order is placed, it must be assigned to one or more fulfillment centers. The

decision of choosing which fulfillment centers satisfy which orders is very critical

and there is an opportunity for the retailer to significantly reduce shipping costs

by making the right decisions. In our research, we use a combination of discrete

event simulation and optimization to investigate the effects of different strategies

and compare their effectiveness.

2 - The Value Of Aggregated Information Sharing In Supply Chains

Vladimir Kovtun, Yeshiva University Syms School of Business,

New York, NY,

vladimir.kovtun@yu.edu

We study a two-stage supply chain where the retailer’s order is the aggregate of

two stationary ARMA processes. We determine when there is value to sharing the

individual processes and when there is additional value to sharing the shocks. We

also determine the supplier’s mean squared forecast error under no sharing,

process sharing, and shock sharing. We find instances when process sharing has

no value which are not present in earlier literature.

3 - Coordination Of The Supply Chain With Quality Improvement And

Customer Returns

Xinghao Yan, Western University, London, ON, Canada. Contact:

xyan@ivey.uwo.ca

We study a supply chain with both quality improvement and customer returns.

We analyze the retailer’s incentive for refund price and the supplier’s incentive for

quality improvement. We also design coordinating contracts for the supply chain,

which is influenced by several factors: contract format, profit negotiation, and

first-mover right.

SD41

207C-MCC

Financial Engineering and Risk Management

Sponsored: Financial Services

Sponsored Session

Chair: Ning Cai, Hong Kong University of Science and Technology,

Clear Water Bay, Kowloon, Hong Kong, China,

ningcai@ust.hk

Co-Chair: Yingda Song, University of Science and Technology of China,

Jinzhai Road, Hefei, 230026, China,

songyd@ustc.edu.cn

1 - Simulating Risk Measures

Steven Kou, National University of Singapore,

matsteve@nus.edu.sg

Risk measures, such as value-at-risk and expected shortfall, are widely used in

risk management. We propose a simple general framework, allowing dependent

samples, to compute these risk measures via simulation. The framework consists

of two steps: In the C-step, we control the relative error in the simulation by

computing the necessary sample size needed for simulation, using a newly

derived asymptotic expansion of the relative errors for dependent samples; in the

S-step, the risk measures are computed by using sorting algorithms. Numerical

experiments indicate that the algorithm is efficient even at the 0.001 quantile

level. This is a joint work with Wei Jiang.

2 - Valuation Of Path-dependent Equity And Credit Derivatives

Ning Cai, Hong Kong University of Science & Technology,

ningcai@ust.hk

We study the pricing problems of path-dependent equity and credit derivatives

within a general hybrid equity-credit framework, i.e., under generalized jump to

default extended exponential Levy models with local volatilities. More precisely,

under this general model, we propose a unified approach to pricing various equity

derivatives and credit derivatives, including defaultable corporate bonds,

European options, barrier options, CDS, and EDS. Numerical results indicate that

our pricing methods are accurate, efficient, and easy to implement. This is joint

work with Haohong Lin from HKUST.

3 - A Unified Framework For Options Pricing Under Regime

Switching Models

Yingda Song, University of Science and Technology of China,

Hefei, China,

songyd@ustc.edu.cn

Regime changes are prevalent in the financial markets, yet it is challenging to

price options in presence of regime switching. In this talk, we provide a unified

framework for pricing options under a wide class of regime switching models.

Based on our framework, we study the effects of regime switching on the prices

and hedge parameters of various types of options, as well as the yield spread of a

structural credit model.

SD41