2016 INFORMS Annual Meeting Program

WA09

INFORMS Nashville – 2016

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, jcruz@business.uconn.edu 1 - Social Responsibility Investments: Financial Networks Analysis Jose Cruz, University of Connecticut, jcruz@business.uconn.edu 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, trdanderson@txwes.edu 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, cmituartevillarreal@miners.utep.edu, 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 Chair: Alexandra M Newman, Colorado School of Mines, 1104 Maple Street, Golden, CO, 80401, United States, anewman@mines.edu 1 - Optimal Stockpiling Strategies In Open Pit Mining Mojtaba Rezakhah, Colorado School of Mines, mrezakha@mines.edu 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, renaud.chicoisne@gmail.com 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. Resources I Mining Sponsored Session

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, adrien.rimele@polymtl.ca, 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 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. 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, krokhmal@email.arizona.edu 1 - Analysis Of Budget For Interdiction On Multicommodity Network Flows Neng Fan, University of Arizona, nfan@email.arizona.edu, 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, foad.mahdavi@umb.edu, 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, mwrysz@yahoo.com 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. Jian Zhang, McGill University, Montreal, QC, Canada, jian.zhang9@mail.mcgill.ca, Roussos G. Dimitrakopoulos WA11 104A-MCC

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