2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
479
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Legends B- Omni
Ops Mgt/Marketing IV
Contributed Session
Chair: Zhenyu Gao, Tsinghua University, Room 430B, Zijing
Department #14, Beijing, 100084, China,
1 - Omni-channel Retail In The Presence Of Operational Frictions
Xiaomeng Guo, Assistant Professor, The Hong Kong Polytechnic
University, M628, Li Ka Shing Tower, Hung Hom, Kowloon, Hong
Kong, , Panos Kouvelis, Danko Turcic
Some firms are implementing omni-channel strategies by offering consistent
products and prices across their multiple channels, and some other firms
essentially prevent seamless transition between different channels. Our paper
provides a game-theoretical model to compare the traditional multi-channel and
omni-channel strategies by focusing on product and price consistency.
2 - The Study About Crowdfunding Flight
Zihao Zhang, Master, University of Science and Technology of
China, 96 Jinzhai Road, Management Research Building
613,Room, Hefei, 230026, China, ,
Liuyi Ling
Airline may have a loss when passenger load factor is very low due to high
we try to solve the problem with crowdfunding.The study investigates
the optimal pricing decision and other decisions about crowdfunding for OTA and
airline with Stackelberg game.Results indicate that OTA can determines the
optimal price and the lowest tickets sales to maximize its profit,in addition,we can
get that lead time will be decided by rent and price. Airline will find the optimal
rent according to decisions of OTA. The study also establish a contract to
coordinate the supply chain consisting of OTA and airline.
3 - Equilibrium Power Structures In The Presence Of
Stochastic Learning
Guowei Liu, Tianjin University, 92 Weijin Road, Nankai District,
Tianjin, 300072, China, Yunchuan Liu,
Jianxiong Zhang
This paper studies equilibrium power structures in a two-period model, where a
manufacturer produces a product with stochastic batch learning and sells it to end
consumers through a retailer facing a linear demand. The manufacturer and the
retailer can implement a dynamic or commitment contract over both periods. We
show that when the learning efficiency is sufficiently high, Vertical Nash and
Retailer Stackelberg are the equilibrium power structures under the dynamic and
commitment contracts, respectively. Meanwhile, the equilibrium power structures
are beneficial to consumers. We also extend our main model to the continuous
learning and non-linear demand cases.
4 - Storage Assignment In Mobile Fulfillment System
Zhenyu Gao, Tsinghua University, 14#430, Zijing Department,
Beijing, 100084, China,
Chen Wang
In the thriving E-commerce market with expanding scale of customers and items,
fulfilling large volume of small orders accounts for most of the operational cost.
The mobile fulfillment system provided by Amazon dispatches large scale of
robots to assemble multiple inventory pods with items needed simultaneously,
which makes storage assignment more flexible by storing multiple items in one
pod and saves cost significantly compared to traditional warehouses. We extract
correlation information among items with factorization machines, which is then
integrated into a clustering model for the assignment solution. Algorithms are
developed both for the factorization machine and assignment model.
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Legends D- Omni
Supply Chain Optimization
Contributed Session
Chair: Mohammad Komaki, Case Western Reserve University, 10900
Euclid Avenue, Cleveland, OH, 44106, United States,
1 - Dynamic Decision Making In A Two Echelon Repairable Inventory
System With Purchase And Order Options
Rana Afzali-Baghdadabadi, Operation Researcher, General Motors,
2462 John R Rd, # 107, Troy, MI, 48083, United States,
, Wooseung Jang
In this study, we consider a two echelon repairable parts inventory system, where
emergency purchasing and ordering from a central warehouse are allowed to
deliver high service levels to customers. A dynamic decision making model is
developed that minimizes the system’s operational costs, including transportation,
stocking and purchasing. The numerical experiments show the benefits of
purchasing and ordering options in the systems with high penalty costs and long
repair times. The benefits are more significant in systems with tight inventories.
Our analysis identifies the best inventory levels that minimize both the
operational costs and the initial investments at the stock location.
2 - Procurement Under Price Uncertainty – An Analysis Of
Operational Hedging Strategies
Ashutosh Sarkar, Associate Professor, Indian Institute of
Management Kozhikode, IIM Campus, Kunnamangalam,
Kozhikode, Kerala, Kozhikode, 673570, India,
Goutam Sutar, Arun Kumar Misra
Consider a manufacturer procuring one of its raw materials from overseas
sources. The manufacturer, while facing the risks of price uncertainty due to
exchange rate fluctuations, needs to decide the timing, the source and the
quantity of purchase. We modeled the manufacturer’s decision problem as a
multi-period inventory problem and showed that the (s, S) policy is optimal when
the manufacturer buys only once during the planning horizon. We also evaluated
various operational hedging strategies like, switching, postponement and
switching with financial options.
3 - Additive Manufacturing In A Bio-medical Supply Chain:
A Continuous Approximation Approach
Adindu Emelogu, PhD Student, Mississippi State University, Dept
of Industrial & Systems Engineering, 479-2 Hardy Road,
Mississippi State, MS, 39762, United States, ,
Sudipta Chowdhury, Mohammad Marufuzzaman, Linkan Bian
The fabrication of biomedical devices close to hospitals via Additive
Manufacturing (AM) technology has been gaining popularity due to the many
potential benefits it provides such as patient-customized parts, fast response, and
reduced delivery cost. However, not much attention has been given to AM
deployment methods which impact the supply chain and the amount reaped of
these benefits. We propose a continuous approximation (CA) model that
quantifies the supply chain network costs of AM-produced biomedical implants.
We present an algorithm that optimizes the location of the AM centers and raw
material inventory to satisfy the customers. We use hospitals in the southeastern
USA as our case study.
4 - Considering Dynamic Demand On The Supply Chain Optimization
Via Bargaining Models On A Common Replenishment Epochs
Environment
José Velásquez, Universidad de los Andes, Calle 44D # 45-86 Int.1
Apto-503, Bogotá, 111321, Colombia,
, Jose Fidel Torres
In this work we present five different linear programing models to coordinate the
supply chain inventories on a single-supplier, single-buyer environment for a
variety of products. We considered the common replenishment epochs (CRE)
approach on different scenarios where the demand faced by the buyer is dynamic.
Depending on the case, one of the actors offers a compensation to the other, in
order to accept a strategy for a fixed replenishment period. Finally, we conducted
a numerical study to evaluate the benefits of the proposed coordination strategies.
5 - Heuristic Algorithm For Multi-criteria Procurement In
Energy Systems
Mohammad Komaki, Case Western Reserve University,
10900 Euclid Avenue, Cleveland, OH, 44106, United States,
Each distributed energy system has several agents, including customer, storage
units, and energy source centers that produce energy. Each of these agents are
connected to other agents either directly or through other agents and these
connections form a network called energy distribution network. To find the
optimal route, several heuristic algorithms have been developed. All of the
developed algorithms are for a single objective function. However, in reality,
decision-makers have to consider several criteria simultaneously. Therefore, the
problem is a multi-criteria problem. In this study, we propose multi-criteria
heuristic algorithm based on Dijkstra’s algorithm.
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