2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
366
WA09
103B-MCC
Sustainable and Responsible Supply Chain
Management II
Sponsored: Energy, Natural Res & the Environment I Environment &
Sustainability
Sponsored Session
Chair: Jose Cruz, Associate Professor, University of Connecticut, 100
Constitution Plaza, West Hartford, CT, 06103, United States,
1 - Social Responsibility Investments: Financial Networks Analysis
Jose Cruz, University of Connecticut,
This paper develops a network equilibrium model in conjunction with capital
asset pricing model (CAPM) and the net present value (NPV) to determine the
optimal portfolio, prices, profits, and equity values of financial network firms
under financial risks and economic uncertainty. We investigate how social
responsible financial investment decisions affect the values of interconnected
financial firms from a network perspective. We model the behavior of the
decision-makers, derive the equilibrium conditions, and establish the variational
inequality formulation.
2 - Corporate Environmental And Social Responsibility In Supply
Chains: Exploring Actions And Performance
Trisha Anderson, Texas Wesleyan University,
A company’s financial strength (doing good in the market place) is based on the
social reputation of the company. We study the level of corporate social
responsibility and performance in Environmental and Social Corporate Social
Responsible activities from the period 2009-2013. We investigate the level of
involvement in each factor over time and determine the relationships between
the CSR factors for the major supply chain players.
3 - Economic Generation Dispatch: A Viral Approach
Carlos Marco Ituarte-Villarreal, SWCA Environmental
Consultants, El Paso, TX, 79912, United States,
, Francisco O Aguirre
The authors present a hybrid Viral Systems Algorithm-Universal Generating
Function approach to solve the multiple-objective network-constrained economic
reallocation of generation resources problem. The here proposed algorithm
considers not only the economic resource dispatch and reliability system
restrictions, but also takes into account environmental constraints, particularly
mass and rate carbon dioxide and nitrogen oxides emissions.
WA10
103C-MCC
Open Pit and Supply Chain Mine Planning
Sponsored: Energy, Natural Res & the Environment, Natural
Resources I Mining
Sponsored Session
Chair: Alexandra M Newman, Colorado School of Mines, 1104 Maple
Street, Golden, CO, 80401, United States,
1 - Optimal Stockpiling Strategies In Open Pit Mining
Mojtaba Rezakhah, Colorado School of Mines,
Mines use stockpiles for blending different grades of material, storing excess
mined material until processing capacity is available, or keeping low-grade ore for
possible future processing. We consider stockpiles as part of our open pit mine
scheduling strategy, and propose multipleinteger-linear models to solve the open
pit mine production scheduling problem. Numerical experiments show that
ourproposed models are tractable, and correspond to instances which can be
solved in afew minutes, at most, in contrast to nonlinear models whose instances
fail to solve.
2 - An Aggregation Branching Scheme For The Resource-
constrained Open Pit Mine Scheduling Problem
Renaud Pierre Chicoisne, University of Colorado denver,
For the purpose of production scheduling, open-pit mines are discretized into 3D
arrays known as block models. Production scheduling consists of deciding which
blocks should be extracted and when they should be extracted during the time
horizon. Blocks that are close to the surface should be extracted first, defining a
set of precedence constraints, and capacity constraints limit the production in
each time period. This Resource Constrained Open Pit Mining scheduling problem
(RC-OPM) can be cast as a linear Integer Programming problem. In this work, we
describe a constraint branching that uses special features of RC-OPM to reach an
integer solution when solving the formulation by Branch and Bound.
3 - Heuristic Method For The Stochastic Open-pit Mine Production
Scheduling Problem
Adrien Rimélé, Master’s Student,École Polytechnique de Montréal,
7593 Rue Berri, Montréal, QC, H2R2G8, Canada,
, Michel Gamache,
Roussos Dimitrakopoulos
Long term open-pit mine planning under geological uncertainty can be assessed
with a Stochastic Integer Program. The complexity of such program is so high that
it is usually hopeless to obtain an optimal or at least good feasible solution within
a reasonable time. This work first presents the application of new partial
relaxation strategies to facilitate the resolution by solver using the strong
interconnections of the variables. Then, a topological sorting algorithm is applied
on the fractional obtained schedule to make it fully binary. Tested on a real
deposit, the methods have given solutions proven to be very close to the
optimality after a short computational time.
4 - A Benders-decomposition-based Method For The Simultaneous
Optimization Of A Mineral Value Chain
Jian Zhang, McGill University, Montreal, QC, Canada,
, Roussos G. Dimitrakopoulos
The classical Benders decomposition is used to solve the simultaneous optimiza-
tion of a mineral value chain. A dynamic bench-pushback generation method is
developed based on the dual price in each benders iteration to optimize the
upstream mine production schedule and a moving window amelioration method
is developed to improved the obtained schedule. The proposed method is tested
in a hypothetical case where the market uncertainty is integrated. The test results
show the importance of integrating market uncertainty in mineral value chain
optimization.
WA11
104A-MCC
Risk Averse Optimization in Networks
Sponsored: Optimization, Network Optimization
Sponsored Session
Chair: Pavlo Krokhmal, Professor, University of Arizona, 1127 E James
E. Rogers Way, Tucson, AZ, 85721, United States,
1 - Analysis Of Budget For Interdiction On Multicommodity
Network Flows
Neng Fan, University of Arizona, ,
Pengfei Zhang
In this talk, we first discuss several versions of network interdiction models for
multicommodity flows, including the model with risk-averse leader. For this kind
of Stackelberg game, where a leader try to destroy the network with limited
budget and the follower seeks the minimum cost of flows to meet the demands in
the resulted network. We will mathematically analyze the interdiction results
under different models and budget limits. Some theories and properties will be
shown. Additionally, some solutions approaches will be proposed.
2 - Detecting Large Risk-averse 2-clubs In Graphs With Random
Edge Failures
Foad Mahdavi Pajouh, University of Massachusetts Boston,
Boston, MA, United States,
Esmaeel Moradi, Balabhaskar Balasundaram
We address the problem of detecting large risk-averse 2-clubs in graphs subject to
probabilistic edge failures, which is modeled as a CVaR-constrained single-stage
stochastic program. We present a new decomposition algorithm based on a
Benders decomposition scheme, which outperforms an algorithm based on an
existing decomposition idea on random, and real-life biological and social
networks.
3 - Clusters Represent Cliques
Maciej Rysz, Air Force Research Lab,
We propose a solution algorithm for identifying the most central clusters in
graphs and examine its effectiveness when the centrality measure is defined by
betweenness and the clusters represent cliques. Numerical experiments
demonstrating the computational performance of the proposed method are
conducted and compared with results obtained from solving an equivalent mixed
integer programming representation.
WA09