2016 INFORMS Annual Meeting Program

WB59

INFORMS Nashville – 2016

WB57 Music Row 5- Omni Behavioral Aspects of Managing Innovation Sponsored: Behavioral Operations Management Sponsored Session Chair: Evgeny Kagan, Ann Arbor, MI, United States, ekagan@umich.edu Co-Chair: Stephen Leider, University of Michigan, Ann Arbor, MI, United States, leider@umich.edu 1 - When To Hire The First Employee? Behavioral Evidence And Insights Anton Ovchinnikov, Queens University, Kingston, ON, Canada, anton.ovchinnikov@queensu.ca, Beatrice Boulu-Reshef, Charles J Corbett Effectively any entrepreneur shifts from doing all the work him/herself to hiring someone to do part of that work. We use an analytical model and behavioral experiments to study when entrepreneurs should and do hire their first employee. Understanding both the optimal timing/conditions of hiring and the deviations of the hiring patterns from optima have the potential to provide insights to a very broad spectrum of entrepreneurs at the critical early stage of their new venture formation process. 2 - Managing The Dynamics Of Delegated Search Karthik Ramachandran, Scheller College of Business, Georgia Institute of Technology, karthik.ramachandran@scheller.gatech.edu, Morvarid Rahmani Firms often delegate search for solutions to challenges such as product design, advertisement creation, executive search, etc. We study the dynamics of delegated search. We identify conditions under which the client should use a committed or open-ended approach to evaluating solutions. 3 - Incentives In Startups: Form And Timing Of Equity Contracting Evgeny Kagan, Ross School of Business, University of Michigan, ekagan@umich.edu, William S Lovejoy, Stephen Leider We explore theoretically and experimentally how form and timing of equity contracting affects contribution behavior to the startup. Our experimental findings are consistent with the empirical evidence that equal division is associated with reduced contributions. However, the differences in contributions are mainly driven by self-selection of low-contributors into equal contracts, rather than by the incentive effects of the contracts. We also find that the negotiation process itself may be an important driver of contribution behavior in collaborative work settings. 4 - An Experimental Investigation Of Favour Exchange Under Monetary And Non-monetary Incentives Kyle Hyndman, Naveen Jindal School of Management, UT Dallas, Richardson, TX, United States, KyleB.Hyndman@utdallas.edu, Matthew Embrey, Rudolf Muller We experimentally study a the situation in which subjects must trade favors - costly actions by one person which only benefits another. We are interested in the role of monetary incentives in promoting efficient exchange. Our results show that monetary exchange achieves the most efficient outcome, but that non- monetary exchange can do as well or better provided that the group scores highly on “social value orientation”.

2 - A Convex Relaxation Approach To Strategic Bidding In Nodal Electricity Markets Hamed Mohsenian-Rad, Associate Professor, University of California - Riverside, 900 University Ave, Department of Electrical Engineering, Riverside, CA, 92521, United States, hamed@ee.ucr.edu, Mahdi Ghamkhari, Ashkan Sadeghi Strategic bidding problems in electricity markets are formulated by bi-level optimization problems which are often translated to mixed-integer linear programs (MILPs). In this paper, we instead propose convex programming to solve the strategic bidding problem in nodal electricity markets. Our approach guarantees a feasible and accurate bidding solution, with 99% optimality. While the computation time of the MILP approach grows exponentially as the scheduling horizon or number of random scenarios increases, the computation time of our approach increases rather linearly. 3 - Optimization In Smart Grid With Limited System Observability Sunil K Vuppala, INFOSYS/IIITB, 309, Elil Abode, Mahadevapura, We present optimization of energy management in smart grid in the presence of limited system observability and controllability. We assume at least % of the scheduled demand is followed by the consumers. Remaining (1- )% is arbitrary, assumed adversarial. Bounds are found with min-min / max-max formulations which is LP/ILP problem. Robust bounds are obtained using heuristics. The initial results indicate adversarial bounds of 200% in 10,000 consumer example which is equal to price ratio. 4 - Handling Dynamic Constraints In Power System Optimization Francois Gilbert, Postdoctoral Appointee, Argonne National Laboratory, 9700 S. Cass Avenue, Lemont, IL, 60439, United States, fgilbert@anl.gov, Shrirang G Abhyankar, Hong Zhang, Mihai Anitescu The inclusion of dynamic stability constraints is the nominal objective of many optimization-based power system analyses. In current practice, this is typically done off-line. We present an approach for the on-line inclusion of dynamic constraints in power grid optimization problems. The approach is based on an encapsulation that allows for a loose coupling between the optimization and the numerical simulations. We demonstrate the benefits of the approach on a 118 bus systems, for which we solve an economic dispatch with transient constraints. 5 - Integrating Short-term And Long-term Transmission Expansion Planning Mohammad Majidi-Qadikolai, Graduate Research Assistant, University of Texas-Austin, 3373 Lake Austin Boulevard, Apt D, Austin, TX, 78703, United States, majidi.mohammad@gmail.com, Ross Baldick For long-term transmission expansion planning (LTEP), 10 + years is usually selected as a planning horizon; however short-term planning (STEP) is limited to less than 5 years. Common practice is to run these two planning studies separately. On one hand, the impact of long-term load and generation growth on STEP is ignored, and on the other hand, LTEP cannot represent network configuration changes as a result of STEP that makes LTEP results less realistic. In this paper, we integrate these two planning studies into a single multi-stage TEP and discuss modeling and computational challenges. WB59 Cumberland 1- Omni Drone-Based Logistics Sponsored: TSL, Facility Logistics Sponsored Session Chair: Sudipta Chowdhury, Mississippi State Univ, MSU, Starkville, MS, 39762, United States, sc2603@msstate.edu Co-Chair: Mohammad Marufuzzaman, Mississippi State University, PO Box 9542, Starkville, MS, 39762, United States, marufuzz@dasi.msstate.edu 1 - Drone Routing And Optimization For Wildlife Surveillance Adindu Emelogu, PhD Student, Mississippi State University, 260 McCain Engineering Building, Mississippi State, MS, 39762, United States, aae39@msstate.edu, Sudipta Chowdhury, Mohammad Marufuzzaman, Linkan Bian, Brian Smith The drone is one of the leading edge technologies developed for military applications with the potential of evolving into useful public and private uses. In this study, we investigate the use of drones in the surveillance and monitoring of wildlife population. Such operation is important for several wildlife conservation and animal health infrastructural initiatives. We formulate the surveillance problem as a mixed-integer linear programming model that determines the location of the drone launching stations and the optimal routing of the drone’s to safely survey the target area and minimize the total location, transportation, and energy costs of the system. Outer Ring Road, Bangalore, 560048, India, sunil.vuppala@iiitb.ac.in, Srinivasa Prasanna

WB58 Music Row 6- Omni Energy XIII Contributed Session

Chair: Mohammad Majidi-Qadikolai, Graduate Research Assistant, University of Texas-Austin, 3373 Lake Austin Boulevard, Apt D, Austin, TX, 78703, United States, majidi.mohammad@gmail.com 1 - A Hybrid Top-down, Bottom-up Approach For Saudi Arabia Hossa Almutairi, King Abdullah Petroleum Studies & Research Center (KAPSARC), King Abdullah Petroleum Studies & Research Ce, Airport Road, Riyadh, 11672, Saudi Arabia, hossa.mutairi@kapsarc.org We show how to combine a CGE-like top-down model with a technology-rich bottom-up energy model in a single Mixed Complementarity Problem (MCP). Calibrated on Saudi Arabia’s data, this hybrid model will be used to study the interaction between energy and non-energy sectors and to get insights on the effects of energy policies on the whole Saudi economy.

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