Informs 2015

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INFORMS Philadelphia – 2015
487
WE26
26-Room 403, Marriott
Project Management II
Contributed Session
Chair: Fang Xie, PhD Student, Beihang University, 37 Xueyuan Road,
Haidian District, Beijing, 100191, China,
1 - Estimation of Resource Allocation Patterns in a Portfolio of
Engineering Projects
Vishwanath Hegde, California State University East Bay, 25800
Carlos Bee Blvd, Hayward, CA, 94542, United States of America,
Zinovy Radovilsky
Using historic resource loading data in a multi-project setting, we show that
resource distribution patterns can be captured by parametric regression models,
which can forecast resource distribution during project lifetime using project due
date and other attributes.
2 - Improved Design of CMS by Considering Operators Primary and
Backup Decision-making Styles
Mohammad Rezaei-Malek, University of Tehran, No. 3,
Ganji Alley, North Khosh Street, Tehran, 1457813353, Iran,
Reza Tavakkoli-Moghaddam,
Nima Salehi Sadghiani
This paper considers decision-making style (as an index of operator’s personal
characteristics) in CFP to design an operator-consistent CMS. Decision-making
style not only influences the interaction of two operators, but also affects the
work that operator does on a machine, and these interactions both need to
observe consistency. Hence, this paper presents a mathematical model for CFP
that considers consistency between each two operators and consistency between
operator and assigned task.
3 - Reactive Project Scheduling with a Cash Flow Balanced Objective
Minjing Ning, Xi’an Jiaotong University, No.28, Xianning West
Road, Xi’an, China, , Zhengwen He
This paper investigates reactive project scheduling which may be used to repair
project schedules that suffer from multiple activity duration disruptions during
project execution. The objective is to minimize the cumulative cash flow gap of
the contractor in the real executing process of the project.
4 - Robust Scheduling of the Resource-constrained DTCTP with
Uncertain Activity Costs
Fang Xie, PhD Student, Beihang University, 37 Xueyuan Road,
Haidian District, Beijing, 100191, China,
Zhe Xu
We investigate the resource-constrained discrete time/cost trade-off problem in
which the activity costs are stochastic and the objective is to construct a robust
baseline schedule that maximizes the probability of completing the project within
the given budget. Two algorithms for solving this problem are presented. We
compare the two algorithms and analyze the impact of different factors through
conducting experiments on a set of instances generated from the PSPLIB.
5 - Project Management And Quality Data Challenges
for IoT Systems
Michael Chuang, SUNY - New Paltz, 1 Hawk Dr, New Paltz,
United States of America, Kuan-Tsae
Huang
Internet of Things (IoT) has shown its potentials to be employed to scenarios of
Industry 4.0. Caterpillar installs sensors and telematics in its products. AzTrong
uses embedded sensors to allow for bidirectional communication over production
lines. Collected data enable remote repair and service to make appropriate deci-
sions, resulting in increased manufacturing uptime and improved customer serv-
ice. How to apply project management to manage IoT becomes an important but
uncharted topic.
WE27
27-Room 404, Marriott
Multicriteria Decision Making II
Contributed Session
Chair: Gang Wang, Assistant Professor, UMass Dartmouth, 285
Westport Road, Room 214, CCB, North Dartmouth, MA, 02747,
United States of America,
1 - A Game Theoretic Approach to Energy Policy Making with
Multiple Objectives
Busra Keles, University of Miami, 1251 Memorial Drive,
Department of Industrial Engineering, Coral Gables, FL, 33146,
United States of America, , Murat Erkoc,
Nurcin Celik, Mahide Kucuk, Yalcin Kucuk
We develop a two-stage decision making model on how a governmental agency
can build and incentivize its energy policy across service providers. The agency, as
the Stackelberg leader, has multiple objectives related to economic concerns,
environment, and energy surety. The agency sets penalties and limits to which
the power companies respond by choosing their investment and production
strategies. We develop a model that integrates the Successive Weighted Sum
method into the policy making game.
2 - A Heuristic Based on Qualitative Information for Territorial
Partitioning Problems
Salem Chakhar, Dr, Portsmouth Business School,
Portland Building, Portland Street, Portsmouth, PO1 3AH,
United Kingdom, , Maria Barbati,
Carmela Piccolo, Giuseppe Bruno
This presentation proposes a heuristic to solve territorial partitioning problems. It
uses as input a tree data structure, previously constructed based on qualitative
information. This qualitative evaluation is grounded on several criteria and takes
the form of a qualitative scale with a finite set of evaluation levels. The heuristic is
illustrated using real-world data relative to Ile-de-France region in France.
3 - A Bi-Level Decentralized Programming for Setting Differential
Subsidy Rate of Taiwan’s Waste Printer
Jiun-Yu Yang, Master Student, Tamkang University,
151 Yingzhuan Rd., New Taipei, 25137, Taiwan - ROC,
, Hsu-shih Shih
This study uses bi-level decentralized programming for setting differential
subsidies on the recycling plants in Taiwan. The case of waste printers is
illustrated. The results show that the differential subsides on recycling plants can
achieve a higher recycling rate.
4 - Markov Method for Assessing Utility Functions
Baback Vaziri, Purdue University, 315 N. Grant St., West
Lafayette, IN, United States of America, ,
Yuehwern Yih, Tom Morin, Mark Lehto
Multiattribute value functions are a useful tool for decision makers. Many
methods directly obtain information from the decision maker regarding the
preferences of attributes. We propose an alternative approach, which will reverse
engineer the weights of the value function. We use the results of the preferences
of alternatives in conjunction with a Markov-based ranking method to develop a
rating vector of attributes.
5 - Operations Scheduling in Reverse Supply Chains:
Delivery Deadlines and Identical Demand
Gang Wang, Assistant Professor, UMass Dartmouth, 285 Westport
Road, Room 214, CCB, North Dartmouth, MA, 02747, United
States of America, , Angappa Gunasekaran
This study addresses an integrated operations scheduling problem of reverse
supply chains with delivery deadlines. The problem is to determine shipping
quantities from collectors to the manufacturer and the assignment of demand
points, subject to the capacity constrains of both the collectors and the
manufacturer.
WE29
29-Room 406, Marriott
Big Data: Inference and Prediction
Sponsor: Analytics
Sponsored Session
Chair: Rob Lantz, Senior Manager Of Operations Analysis, Novetta
Solutions, 8618 Westwood Center Drive, Suite 315, Vienna, VA, 22182,
United States of America,
1 - Detecting Unknown Threats through Social Network Analysis
Matt Teschke, Senior Quantitative Consultant, Novetta, 7921
Jones Branch Drive, 5th Floor, McLean, VA, 22102,
United States of America, , Jennifer Stave
A common impediment to the analysis of networks is the determination of risk
relative to particular actors within the network. Using insights from the field of
SNA in addition to an understanding of the challenges faced by the analyst,
entities can be prioritized for investigation. This network-centric approach assigns
risk based on an assessment of an entity’s characteristics and activity using an
eigenvector centrality algorithm, of which Google’s PageRank algorithm is one
application.
WE29