Informs 2015

356 / 552

INFORMS Philadelphia – 2015
354
TD26
26-Room 403, Marriott
Production and Scheduling I
Contributed Session
Chair: Srimathy Mohan, Associate Professor, Arizona State University,
Department of Supply Chain Management, Tempe, AZ,
United States of America,
1 - Weekly Production Planning on the Basis of Average
Value-at-Risk by Shapley Value
Nobuyuki Ueno, Hiroshima University of Economics, 5-37-1 Gion
Asaminami-ku, Hiroshima, Japan, ,
Hiroshi Morita, Koji Okuhara
Under demand uncertainty,they used stock-out ratio for estimating the risk. In
this presentation, we propose a formulation for weekly production planning
problem that reflects the AVaR (Average value-at-risk) for weighing tail risk and a
solution by Shapley value. The characteristics of the solution procedure is proved.
It has the features that it does not require strict probability distribution of stock-
out and it enables an extension to the case where demand for each period is
correlated.
2 - A Generalized Dantzig-Wolfe Decomposition Algorithm for Mixed
Integer Programming Problems
Xue Lu, London School of Economics and Political Science,
Houghton Street, London, WC2A 2AE, United Kingdom,
Zeger Degraeve
We propose a generalized Dantzig-Wolfe decomposition algorithm for mixed
integer programming. By generating copy variables, we can reformulate the
original problem to have a diagonal structure which is amendable to the Dantzig-
Wolfe decomposition. We apply the proposed algorithm to multi-level capacitated
lot sizing problem and production routing problem. Rigorous computational
results show that our algorithm provides a tighter bound of the optimal solution
than all the existing methods.
3 - The Impact of Postponement Practices on the Lot-sizing
Decisions of a Wine Bottling Plant
Sergio Maturana, Professor, Pontificia Universidad Catolica de
Chile, Vicuna Mackenna 4860, Santiago, Chile,
Mauricio Varas
Export-focused wineries face a difficult problem when planning their bottling
lines due to the number of different products they have to bottle and label. A way
of reducing misallocation due to demand variability is by postponing the labeling
process. We propose two MIP planning models that support tactical lot-sizing
decisions. We tested both models in a rolling horizon framework, under different
conditions of capacity tightness, horizon length, and demand uncertainty and we
report the results.
4 - Scheduling of Maximizing Total Job Value with Machine
Availability Constraint
Eun-Seok Kim, Middlesex University, The Burroughs, London,
NW4 4BT, United Kingdom, Joonyup Eun
We study a single machine scheduling problem of maximizing total job value with
machine availability constraint. The value of each job is given as a non-increasing
step function of its completion time. We develop a branch-and-bound algorithm
and a heuristic algorithm for the problem. Finally, we perform computational
experiments showing that the developed algorithms provide efficient and effective
solutions.
TD27
27-Room 404, Marriott
Applications of Multi-objective Optimization
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 - A Hybrid Decision Making Approach for Multi-Objective
Infrastructure Planning
Hana Chmielewski, North Carolina State University,
Campus Box 7908, Raleigh, NC, 27695, United States of America,
Ranji Ranjithan
A hybrid approach using evolutionary computation and dynamic programming is
used to optimize investments and operational decisions in a water supply case
study system. Solutions are categorized by network centralization metrics, and
analyzed with respect to multiple planning objectives.
2 - Evaluating Lignocellulosic Biomass Supply Chains Considering a
Multi-objective of Optimizing Cost
Burton English, Professor, The University of Tennessee, 2621
Morgan Hall, Knoxville, TN, 37922, United States of America,
, James Larson, Edward Yu, Jia Zhong
A switchgrass supply chain that considers the optimization of cost, GHG emissions
and soil erosion for a cellulosic biofuel plant is developed. Using an augmented
epsilon constraint multi-objective optimization model and a compromise solution
method, along with high-resolution spatial data the optimal placement of
feedstock supply chains can be estimated. Spatial characteristics, including land
coverage and infrastructure availability, are crucial to both the cost and the
environmental results.
TD28
28-Room 405, Marriott
Dynamic Matching Markets
Cluster: Auctions
Invited Session
Chair: John Dickerson, CMU, 9219 Gates-Hillman Center, Pittsburgh,
PA, 15213, United States of America,
1 - Global Kidney Exchange
Afshin Nikzad, Stanford University, 37 Angell Court,
Apt 116, Stanford, CA, 94305, United States of America,
, Mohammad Akbarpour, Alvin Roth
In some countries, many patients die after a few weeks of diagnosis mainly
because the costs of kidney transplantation and dialysis are beyond the reach of
most citizens. We analyze the two proposals in which patients with financial
restrictions who have willing donors participate in kidney exchange without
paying for surgery. Our proposals can save thousands of patients, while
substantially decreasing the average dialysis costs; in particular, we prove that
they are “self-financing”
2 - Matching with Stochastic Arrival
Neil Thakral, Harvard, 1805 Cambridge Street, Cambridge, MA,
United States of America,
We study matching in a dynamic setting, with applications to public-housing
allocation. Objects of different types that arrive stochastically over time must be
allocated to agents in a queue. When objects share priorities over agents, we
propose an efficient, envy-free, and strategy-proof mechanism. The mechanism
continues to satisfy these properties if and only if the priority relations are acyclic.
Estimated welfare gains over existing housing-allocation procedures exceed
$5000 per applicant.
3 - Dynamic Kidney Exchange with Heterogeneous Types
Maximilien Burq, Student, MIT, 77 Massachusetts Avenue,
Cambridge, MA, 02139, United States of America,
, Itai Ashlagi, Vahideh Manshadi, Patrick Jaillet
Kidney exchange programs face growing number of highly sensitized patients. We
develop an online model that models such heterogeneity, and we prove that
having some easy-to-match patients in the pool greatly reduces waiting times
both in the presence of bilateral matching and chain matching. We provide
simulations showing that some prioritizing leads to improved overall efficiency.
4 - Competing Dynamic Matching Markets
Sanmay Das, WUSTL, One Brookings Dr, CB 1045,
St. Louis, MO, 63130, United States of America,
John Dickerson, Zhuoshu Li,
Tuomas Sandholm
We extend a framework of dynamic matching due to Akbarpour et al. to
characterize outcomes in cases where two rival matching markets compete. One
market matches quickly while the other builds thickness by matching slowly. We
present analytical and simulation results, both in general and for kidney
exchange, demonstrating that rival markets increase overall loss compared to a
single market that builds thickness.
TD26