Informs 2015

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INFORMS Philadelphia – 2015
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5 - Open Priority Scheduling Protocol for Sourcing and
Supply Management
Katariina Kemppainen, School of Business, Aalto University,
Runeberginkatu 22-24, Helsinki, 00076 Aalt, Finland,
Ari Vepsäläinen
Are you happy with the first-come-first-served priority rule when ordering goods
online? The extensive scheduling literature has few answers from real-life
applications, whereas in procurement case studies abound but theoretical
analyses are few. We propose an open protocol for manufacturing and
procurement which beats consistently not only FCFS but any other rule. It offers
a sophisticated solution for one universal rule. Our protocol is backed up with
simulation results and real-life cases.
WA27
27-Room 404, Marriott
Multi-objective Optimization and Applications
Sponsor: Multiple Criteria Decision Making
Sponsored Session
Chair: Matthias Ehrgott, Professor, Department: Management Science,
Lancaster University, The Management School, Lancaster, 00, LA1 4YX,
United Kingdom,
1 - Ultra-high-dimensional Optimization for Trade Space Exploration:
Challenges and Lessons Learned
Matthew Hoffman, Sandia National Laboratories, P.O. Box 5800
MS 1188, Albuquerque, NM, 87185-1188, United States of
America, Alexander Dessanti,
Stephen Henry, Jack Gauthier
In projects with many conflicting stakeholder objectives, negotiating compromise
requires understanding tradeoffs. Existing multiobjective approaches build
“coalitions” of objectives to reduce dimensionality – either explicitly via
aggregation, or implicitly – which favors solutions that compromise across many
objectives, but can severely obfuscate or distort the tradeoffs between them. We
discuss our progress thus far in true ultra-high-dimensional optimization for trade
space exploration.
2 - Special Constraint Treatment for Multi-objective Optimization
Sijie Liu, Graduate Student, University of Alabama, 714 1/2 12th
St. B, Tuscaloosa, AL, 35401, United States of America,
Several methods has been developed for finding pareto set and pareto front for
multi-linear objective optimization problem subjective to one additional special
constraint(such as bi-linear constraint or N-linear constraint) over a bounded
interval domain subjective to linear equality constraint. These methods provide us
fast approaches to plot the entire pareto frontier. Algorithms have been proved
and numerical results demonstrate the effectiveness of these methods.
3 - A Nonparametric Approach to the Multi-Objective Sequential
Decision Problem
Young H. Chun, Professor, Louisiana State University,
E. J. Ourso College of Business, Baton Rouge, LA, 70820,
United States of America,
Many choices are presented one at a time. You must decide whether to choose
the current choice and stop the search process or to reject it and move to the next
stage. The decision is irrevocable and each choice is evaluated based on multiple
objectives. We propose a rank-based optimal decision strategy that minimizes the
weighted rank of the selected choice. It can be shown that many sequential
decision problems are special cases of the generalized multi-objective sequential
decision problem.
4 - Deliverable Radiotherapy using Multiobjective Optimisatio and
Column Generation
Matthias Ehrgott, Professor, Department: Management Science,
Lancaster University, The Management School, Lancaster, 00,
LA1 4YX, United Kingdom, ,
Kuan-min Lin
We propose a column generation based approach to compute deliverable
radiotherapy treatment plans based on a multi-objective optimisation problem.
We compute a representative set of non-dominated treatment plans using the
revised normal boundary intersection method. The generation of each non-
dominated treatment plan uses column generation to generate apertures that
directly deliverable, obviating the need for a separate segmentation step that
deteriorates plan quality.
WA28
28-Room 405, Marriott
Bidding Mechanisms
Cluster: Auctions
Invited Session
Chair: Bernardo Quiroga, Assistant Professor, Business and Behavioral
Science, Clemson University, 100 Sirrine Hall, Clemson, SC, 29634,
United States of America,
1 - One-dimensional Strategyproof Facility Location
Itai Feigenbaum, Columbia University, New York, NY,
United States of American, Chun Ye,
Jay Sethuraman
Consider a set of agents on an interval, where a planner wishes to locate a facility
so as to maximize some social benefit function. The agents have linear preferences
over the location of the facility, and their locations are unknown to the planner.
Thus, the planner wishes to locate the facility in a strategyproof manner while
approximating social benefit. We discuss mechanisms, lower bounds, and
characterizations for various versions of this model.
2 - Greening Multi-tenant Data Center Demand Response with
Supply Function Bidding
Niangjun Chen, California Institute of Technology, Pasadena, CA,
United States of American, Adam Wierman,
Shaolei Ren, Xiaoqi Ren
Data centers have become critical resources for emergency demand response
(EDR). In this talk, we focus on “greening” demand response in multi-tenant data
centers by incentivizing tenants’ load reduction and reducing on-site diesel
generation. Our proposed mechanism, ColoEDR, which is based on parameterized
supply function mechanism, provides provably near-optimal efficiency
guarantees, both when tenants are price-taking and when they are price-
anticipating.
3 - Optimal Bidding for Bundles in Sequential Auctions
Karti Puranam, Assistant Professor, La Salle University, 1900 W
Olney Ave, Philadelphia, PA, 19141, United States of America,
, Michael Katehakis
We study the problem of optimal bidding for a firm that in each period procures
items to meet a random demand by participating in a finite sequence of auctions
where in each auction involves bids for bundles of items. We develop a new
model for a firm where its item valuation derives from the sale of the acquired.
We establish monotonicity properties for the value function and the optimal
dynamic bid strategy and we present computations.
4 - Complexity and Transparency in Sealed-bid Procurement
Auctions with Multi-dimensional Bids
Bernardo Quiroga, Assistant Professor, Business and Behavioral
Science, Clemson University, 100 Sirrine Hall, Clemson, SC,
29634, United States of America, ,
Brent Moritz, V. Daniel R. Guide, Jr.
We experimentally analyze A+B (price-and-quality) bidding behavior in two
closely related sealed-bid scenarios: One where the rule to assign the contract is
transparently communicated to bidders before they submit their offers, and
another where the assignment rule is only known to the buyer and not to the
bidders. Our results show substantial losses in terms of social welfare and buyer
surplus as a direct effect of transparency loss in this procurement system.
WA29
29-Room 406, Marriott
Applied Analytics
Sponsor: Analytics
Sponsored Session
Chair: Jon Alt, Assistant Professor, Naval Postgraduate School,
Department of Operations Research, Naval Postgraduate School,
Monterey, CA, 93943, United States of America,
1 - Improved U.S. Army Reserve Stationing using Recruitable
Market Demographics
Nathan Parker, U.S. Army, 4120 Crest Rd, Pebble Beach, CA,
93953, United States of America,
The objective of this work is to develop a model to predict a U.S. Army Reserve
(USAR) unit’s manning level based on the demographics of the unit’s reserve
center recruitable market (RCRM). This study first develops an allocation method
to determine the RCRM available to each reserve center. Classification and
regression models are then developed to determine the ability of the RCRM to
support the reserve center’s manning requirements.
WA27