Boulder, CO, United States

OptTek Systems, Inc.

www.opttek.com
Boulder, CO, United States

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Shortle J.,George Mason University | Rebennack S.,Colorado School of Mines | Glover F.W.,OptTek Systems, Inc.
IEEE Transactions on Power Systems | Year: 2014

The objective of this paper is to determine an optimal plan for expanding the capacity of a power grid in order to minimize the likelihood of a large cascading blackout. Capacity-expansion decisions considered in this paper include the addition of new transmission lines and the addition of capacity to existing lines. We embody these interacting considerations in a simulation optimization model, where the objective is to minimize the probability of a large blackout subject to a budget constraint. The probability of a large-scale blackout is estimated via Monte Carlo simulation of a probabilistic cascading blackout model. Because the events of interest are rare, standard simulation is often intractable from a computational perspective. We apply a variance-reduction technique within the simulation to provide results in a reasonable time frame. Numerical results are given for some small test networks including an IEEE 14-bus test network. A key conclusion is that the different expansion strategies lead to different shapes of the tails of the blackout distributions. In other words, there is a tradeoff between reducing the frequency of small-scale blackouts versus reducing the frequency of large-scale blackouts. © 1969-2012 IEEE.


Wang H.,Texas A&M International University | Kochenberger G.,University of Colorado at Denver | Glover F.,OptTek Systems, Inc.
Computers and Operations Research | Year: 2012

The quadratic knapsack problem (QKP) has been the subject of considerable research in recent years. Despite notable advances in special purpose solution methodologies for QKP, this problem class remains very difficult to solve. With the exception of special cases, the state-of-the-art is limited to addressing problems of a few hundred variables and a single knapsack constraint. In this paper we provide a comparison of quadratic and linear representations of QKP based on test problems with multiple knapsack constraints and up to eight hundred variables. For the linear representations, three standard linearizations are investigated. Both the quadratic and linear models are solved by standard branch-and-cut optimizers available via CPLEX. Our results show that the linear models perform well on small problem instances but for larger problems the quadratic model outperforms the linear models tested both in terms of solution quality and solution time by a wide margin. Moreover, our results demonstrate that QKP instances larger than those previously addressed in the literature as well as instances with multiple constraints can be successfully and efficiently solved by branch and cut methodologies. © 2011 Elsevier Ltd. All rights reserved.


Lu Z.,University of Angers | Hao J.-K.,University of Angers | Glover F.,OptTek Systems, Inc.
Journal of Heuristics | Year: 2011

In this paper, we present an in-depth analysis of neighborhood relations for local search algorithms. Using a curriculum-based course timetabling problem as a case study, we investigate the search capability of four neighborhoods based on three evaluation criteria: percentage of improving neighbors, improvement strength and search steps. This analysis shows clear correlations of the search performance of a neighborhood with these criteria and provides useful insights on the very nature of the neighborhood. This study helps understand why a neighborhood performs better than another one and why and how some neighborhoods can be favorably combined to increase their search power. This study reduces the existing gap between reporting experimental assessments of local search-based algorithms and understanding their behaviors. © Springer Science+Business Media, LLC 2010.


Wang Y.,University of Angers | Lu Z.,Huazhong University of Science and Technology | Glover F.,OptTek Systems, Inc. | Hao J.-K.,University of Angers
Computers and Operations Research | Year: 2013

This paper presents two algorithms combining GRASP and Tabu Search for solving the Unconstrained Binary Quadratic Programming (UBQP) problem. We first propose a simple GRASP-Tabu Search algorithm working with a single solution and then reinforce it by introducing a population management strategy. Both algorithms are based on a dedicated randomized greedy construction heuristic and a tabu search procedure. We show extensive computational results on two sets of 31 large random UBQP instances and one set of 54 structured instances derived from the MaxCut problem. Comparisons with state-of-the-art algorithms demonstrate the efficacy of our proposed algorithms in terms of both solution quality and computational efficiency. It is noteworthy that the reinforced GRASP-Tabu Search algorithm is able to improve the previous best known results for 19 MaxCut instances. © 2011 Elsevier Ltd.


Grant
Agency: National Science Foundation | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 150.00K | Year: 2010

This Small Business Innovation Research (SBIR) Phase I project seeks to design a model and algorithmic approach and develop pilot software as a teaching tool for building proficiency in decision-making and analysis relating to economic and environmental impacts of new initiatives to support economic development planning for American Indian Reservation Communities. This work adds innovations in optimizing technologies, yielding capabilities for entrepreneurial education that do not currently exist. The software is anticipated to have widespread application for improving economic performance and quality of life on Native American Reservations. The broader impacts of this research include the potential to: a) improve entrepreneurial education applications for economic development planning; b) support significant social and economic initiatives; c) design a more effective approach using simulation and optimization techniques to economic planning; d) develop and market commercial-grade software that may be applied to other high-risk, highly complex development environments; e) attract downstream funding from sources including private capital firms, non-government agencies, and business alliance partners as it significantly increases economic performance; f) add to the body of knowledge in education applications, economic planning, and decision sciences that may be leveraged to enable additional research and development.


Grant
Agency: Department of Defense | Branch: Missile Defense Agency | Program: STTR | Phase: Phase I | Award Amount: 99.88K | Year: 2013

OptTek Systems, Inc (OptTek), proposes an affordable, effective UQ capability for both legacy and new BMDS M & S. The OptTek Team includes research institution partner Oak Ridge National Laboratory (ORNL) and subcontractor RTSync Corporation (RTSync). The proposed BMDS M & S UQ capability maximizes insertability into existing and future MDA BMDS M & S-supported Event processes, analysis methods, architectures, simulations and frameworks. The OptTek Team will deliver systems engineering artifacts for an objective end-state BMDS M & S UQ Reference Architecture configured on RTSync"s proven Discrete Event Systems Specification (DEVS) for straightforward insertion into existing and new BMDS M & S tools. The BMDS M & S UQ capability builds on the ORNL"s methods and experience with Quantification of Margins and Uncertainties (QMU) to provide an objective measure of confidence in M & S-based results. The OptTek Team proposes innovative epistemic UQ by leveraging the Government"s prior investment in the OptDef BMDS Simulation Optimization. In the Phase I Option, the OptTek Team proposes a prototype demonstration of joint epistemic and aleatoric UQ and QMU using existing MDA BMDS M & S tools, OptDef with the Monte Carlo simulation capability in the Extended Air Defense Simulation (EADSIM). OptTek"s 20-year track record commercializing advanced algorithms and SBIR products maximizes the likelihood of commercialization success.


This Small Business Innovation Research (SBIR) Phase I project seeks to design a model and algorithmic approach and develop pilot software as a teaching tool for building proficiency in decision-making and analysis relating to economic and environmental impacts of new initiatives to support economic development planning for American Indian Reservation Communities. This work adds innovations in optimizing technologies, yielding capabilities for entrepreneurial education that do not currently exist. The software is anticipated to have widespread application for improving economic performance and quality of life on Native American Reservations.

The broader impacts of this research include the potential to: a) improve entrepreneurial education applications for economic development planning; b) support significant social and economic initiatives; c) design a more effective approach using simulation and optimization techniques to economic planning; d) develop and market commercial-grade software that may be applied to other high-risk, highly complex development environments; e) attract downstream funding from sources including private capital firms, non-government agencies, and business alliance partners as it significantly increases economic performance; f) add to the body of knowledge in education applications, economic planning, and decision sciences that may be leveraged to enable additional research and development.


Grant
Agency: Department of Defense | Branch: Missile Defense Agency | Program: SBIR | Phase: Phase II | Award Amount: 749.93K | Year: 2010

OptTek proposes to create a new methodology and tool set, "OptDef," to provide MDA a capability to optimize Ballistic Missile Defense systems-a capability that will enable MDA to answer credibly not only "what if?", but also "what's best?" and "why this and not that?" OptDef will build on proven OptTek-proprietary technologies in simulation optimization that will leverage MDA's investment in such credible and accredited BMDS-level performance tools as SABER, CAPS, I-SIM, DE Sim and LIDS. OptDef will significantly increase the effective utility of BMDS simulation models allowing analysts to optimize more than 10,000 continuous and/or discrete system decision variables. OptDef's technology will seamlessly integrate with MDA simulation systems without modifying or affecting the simulation systems in any way. Toward fulfillment of this SBIR's long-term objective, the technical objectives for this proposal fall into three categories - Software Integration, Optimization Technology, and System Analyses. The Software Integration component will address the mechanics of coupling OptDef with DSA and other systems of simulations. The Optimization Technology objectives will focus on development of specific algorithms and techniques to enhance the utility of OptDef for MDA applications. Finally, the System Analyses component of this project will provide analysis support for the war-fighter using OptDef.


Grant
Agency: Department of Defense | Branch: Missile Defense Agency | Program: SBIR | Phase: Phase II | Award Amount: 2.55M | Year: 2010

OptTek proposes to create a new methodology and tool set, “OptDef,” to provide MDA a capability to optimize Ballistic Missile Defense systems—a capability that will enable MDA to answer credibly not only “what if?”, but also “what’s best?” and “why this and not that?” OptDef will build on proven OptTek-proprietary technologies in simulation optimization that will leverage MDA’s investment in such credible and accredited BMDS-level performance tools as SABER, CAPS, I-SIM, DE Sim and LIDS. OptDef will significantly increase the effective utility of BMDS simulation models allowing analysts to optimize more than 10,000 continuous and/or discrete system decision variables. OptDef’s technology will seamlessly integrate with MDA simulation systems without modifying or affecting the simulation systems in any way. Toward fulfillment of this SBIR’s long-term objective, the technical objectives for this proposal fall into three categories – Software Integration, Optimization Technology, and System Analyses. The Software Integration component will address the mechanics of coupling OptDef with DSA and other systems of simulations. The Optimization Technology objectives will focus on development of specific algorithms and techniques to enhance the utility of OptDef for MDA applications. Finally, the System Analyses component of this project will provide analysis support for the war-fighter using OptDef.


Grant
Agency: Department of Health and Human Services | Branch: | Program: SBIR | Phase: Phase II | Award Amount: 749.98K | Year: 2010

DESCRIPTION (provided by applicant): Statistical databases for public use pose a critical problem: how to make the data available for analysis without disclosing information that would infringe on privacy, violate confidentiality, or endanger national security. Organizations in the public and private sectors have a major stake in this confidentiality protection problem, given the fact that access to data is essential for advancing research and formulating policy. Yet, the possibility of extracting certain sensitive elements of information from the data can jeopardize the welfare of these organizations and potentially, the welfare of the society in which they operate. The challenge is, therefore, to represent the data in a form that permits accurate analysis for supporting research, decision-making and policy initiatives, while preventing an unscrupulous or ill- intentioned party from exploiting the data for harmful consequences. The objective of this project is to develop a practical, computer-based framework for assessing, measuring, and mitigating disclosure risk in public use data. Our proposed framework, called OptShield, overcomes the disadvantages found in currently deployed disclosure limitation methods. We achieve this by combining perturbation and suppression methods with optimal switching of sensitive records at the micro-data level, to produce a method that protects confidentiality while preserving data integrity. In Phase II we are proposing to continue algorithmic and software development to achieve the objective of a working prototype of the software and service. This software will serve as the core technology to provide an application for a broad market in which customers have a major stake in confidentiality protection. The application we ultimately plan to offer in Phase III will consist of a three-phased approach to the disclosure limitation problem: (1) Assess a user's qualitative and quantitative disclosure risks inherent in the organization's data publishing and sharing plans; (2) Measure the disclosure risks in a user's proposed data products; and (3) Protect the user's data by applying the appropriate disclosure limitation techniques. PUBLIC HEALTH RELEVANCE: Public health organizations that collect and share sensitive data are apprehensive about the risk of inadvertently disclosing confidential information, given the fact that access to their data is essential for advancing research and formulating policy. Yet, the possibility of extracting certain vulnerable elements of information from the data, even after personal identifiers have been removed, can jeopardize the welfare of these organizations and potentially the welfare of the society in which they operate. Within the US Department of Health and Human Services, for example, preserving the confidentiality of records in order to continue to elicit information from the American people and from health care providers is a matter of primary concern (CDC/NCHS confidentiality guide). OptTek Systems, Inc. (OptTek) is developing a comprehensive framework designed to help public health and other organizations to avoid the disclosure of confidential information in public-use data. The application consists of a three-phased approach to the disclosure limitation problem: (1) Assess a user's qualitative and quantitative disclosure risks; (2) Measure the disclosure risks in a user's proposed data publishing and sharing plans; and (3) Protect the user's data by applying the appropriate disclosure limitation techniques.

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