Informs 2015

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INFORMS Philadelphia – 2015
391
WA55
55-Room 108B, CC
Forecasting
Contributed Session
Chair: Arnd Huchzermeier, WHU-Otto Beisheim School of
Management, Production Management, Burgplatz 2, Vallendar, 56179,
Germany,
1 - Modeling Effects of Price Changes on Sales for Improved
Forecasting and Promotion Planning
Shubhankar Ray, Walmart Labs, 850 Cherry Ave., San Bruno,
CA, 94066, United States of America,
Brian Seaman, Ashin Mukherjee
In online retail, the high sales variability & missing samples makes item-level
estimation of price elasticities unreliable. We use a mixed-effects framework to fit
autoregressive distributed lag models on item groups to get reliable population-
level estimates of short/long-run elasticities while pooling information across
items. This model can be layered with any forecasting model to generate price
sensitive forecasts & can help steer the sales in a desired direction during
promotion planning.
2 - A Better Accuracy Measure than Mean Absolute Percentage Error
Chris Tofallis, Professor of Decison Science, Hertfordshire
Business School, College Lane, Hatfield, AL10 9AB,
United Kingdom,
Although Mean Absolute Percentage Error is widely used, it suffers from bias: its
use in selecting a forecasting method favours methods whose predictions are too
low. We explain why this happens and present an alternative relative accuracy
measure which is unbiased. This measure can be used to estimate prediction
models. Minimum MAPE models do not predict a known statistic. By contrast,
when the proposed metric is used, the resulting least squares regression model
predicts the geometric mean.
3 - Information Sharing in Supply Chains Facing
Autoregressive Demand.
Vladimir Kovtun, Syms School of Business, 215 Lexington
Avenue, New York, NY, 10016, United States of America,
, Avi Giloni, Clifford Hurvich
We introduce a general class of potentially valuable sharing arrangements in a
multi-stage supply chain in which the retailer observes stationary ARMA demand
with respect to Gaussian white noise (shocks). We demonstrate how a typical
supply chain player can create an incentive-compatible sequence of partial-
information shocks (PIS) based on its available information and share these with
an adjacent upstream player, potentially reducing the upstream players lead-time
demand forecast error.
4 - Judgemental Demand Forecasts for Online Sales of a Premium
Bike Manufacturer
Arnd Huchzermeier, WHU-Otto Beisheim School of
Management, Production Management, Burgplatz 2, Vallendar,
56179, Germany, , Christoph Diermann
We present a judgmental demand forecast model for a premium bike
manufacturer selling each season a new collection of products online. Forecast
accuracy could be improved by using a team approach, by de-biasing the expert
forecasts and by selecting the appropriate segmentation of bike types. Forecast
accuracy could be improved by 26% and profit increased by more than 40%.
WA56
56-Room 109A, CC
Operations Management VII
Contributed Session
Chair: Xueyuan Cai, Huazhong University of Science and Technology,
1037Luoyu road, Wuhan, China,
1 - Configurations of Distribution Strategies
Jing Tang, Em-Lyon Business School, 23 Avenue Guy de
Collongueresear, Ecully, 69134, France,
Yeming Gong
Based on 124 quantitative samples with both first-hand and second hand data, as
well as 56 qualitative samples, this paper examines the strategic fit of distribution
strategies from the perspective of configuration theory. We find that the fit
between operational decisions including infrastructural and structural decisions,
and operational competencies including cost and flexibility, has an important
effect on business performance.
2 - Exchange-old-for-new Program: An Incentive to Induce Early
Purchases with Product Rollover
Yongbo Xiao, Associate Professor, Tsinghua University,
School of Economics and Management, Beijing, 100084, China,
Qian Liu
Many customers may choose to wait for new generation of products in face of
product roll-overs. We propose to adopt an exchange-old-for-new program to
induce customers to make early purchase. Starting from the choice behavior of
strategic customers and based on a dynamic programming model, we study the
optimal pricing decision involved in the exchange program.
3 - Model and Algorithms for the Integrated Production and Vehicle
Routing Problem
Ling Liu, Huazhong University of Science & Technology,
1037 Luoyu Road, Wuhan, Hubei, China, Wuhan, China,
In this paper, the integrated production and vehicle routing problem is considered
in a Make-to-Order (MTO) manufacturer, where there is a single machine for
production and limited vehicles with capacity constraints for transportation. The
objective is to determine the decisions about production scheduling,
transportation batching and vehicle routing, to minimize the maximum order
delivery time. An optimal property is proposed and based on the property,an
improved genetic algorithm is developed.
4 - Optimizing Multi-item Joint Replenishment under Stochastic
Demand and Uncertain Leadtime
Xueyi Ai, School of Management, Huazhong University of
Science and Technology, 1037 Luoyu Road, Wuhan, China,
Wuhan, China, , Jinlong Zhang,
Lin Wang
In real-life practice, leadtime uncertainty is a common phenomenon which may
be caused by various factors. The purpose of this paper is to develop a more
realistic joint replenishment model considering both stochastic demand and
uncertain leadtime simultaneously, and propose an improved fruit fly
optimization algorithm (IFOA) to solve the problem, minimizing the long-run
average total costs. Experimentation results show the standard deviation of
leadtime has large effect on the system.
5 - Strategy Comparison of Capacity Allocation in a Supply Chain
with One Dominant Retailer
Xueyuan Cai, Huazhong University of Science and Technology,
1037Luoyu road, Wuhan, China,
Jianbin Li
We consider a distribution system with one supplier and two retailers. The
supplier will implement allocation mechanisms or improve her wholesale price
when the capacity can’t match demand. Conventional wisdom thinks that the
impact to the supplier by “order-inflation” mechanisms is not the same as that by
“truth-telling” mechanisms. But we show that this is not true in our setting
where each retailer faces a oligopoly market and places order to the supplier
considering the capacity constraints.
WA57
57-Room 109B, CC
Electric Transportation Systems Modelling
Sponsor: ENRE – Energy I – Electricity
Sponsored Session
Chair: Ramteen Sioshansi, Associate Professor, The Ohio State
University, Integrated Systems Engineering, 1971 Neil Avenue,
Columbus, OH, 43210, United States of America,
1 - Optimization of Incentive Polices for Plug-in Electric Vehicles
Yu Nie, Northwestern University, Evanston, IL, United States of
American, Mehrnaz Ghamami
High initial purchase prices and the lack of supporting infrastructure are major
hurdles to the adoption of plug-in electric vehicles (PEVs). It is widely recognized
that the government could help break these barriers through incentive policies,
such as offering purchase rebates and funding charging stations. The objective of
this paper is to propose a modeling framework to optimize the design of such
incentive policies.
2 - Incentive-compatible Charging Mechanisms for Plug-in
Electric Vehicles
Mark Nejad, Assistant Professor, University of Oklahoma,
Industrial and Systems Engineering, Norman, OK, United States
of America, , Lena Mashayekhy
We design charging mechanisms for plug-in electric vehicles considering different
charging rates. We prove that our proposed mechanisms are dominant-strategy
incentive compatible, so that EV drivers have no incentive to misreport their
charging requests or their arrival-departure dynamics.
WA57