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Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering

Human Performance Risks And Benefits Of Adaptive Systems On The Flight Deck, Michael C. Dorneich, William Rogers, Stephen D. Whitlow, Robert Demers Nov 2016

Human Performance Risks And Benefits Of Adaptive Systems On The Flight Deck, Michael C. Dorneich, William Rogers, Stephen D. Whitlow, Robert Demers

Industrial and Manufacturing Systems Engineering Publications

Objective. Human performance risks and benefits of adaptive systems were identified through a systematic analysis and pilot evaluation of adaptive system component types and characteristics. Background. As flight-deck automation is able to process ever more types of information in sophisticated ways to identify situations, it is becoming more realistic for adaptive systems to adapt behavior based on their own authority. Method. A framework was developed to describe the types and characteristics of adaptive system components and was used to perform a risk/benefit analysis to identify potential issues. Subsequently, eight representative adaptive system storyboards were developed for an evaluation with ...


Virtual Operator Modeling Method For Excavator Trenching, Yu Du, Michael C. Dorneich, Brian L. Steward Oct 2016

Virtual Operator Modeling Method For Excavator Trenching, Yu Du, Michael C. Dorneich, Brian L. Steward

Industrial and Manufacturing Systems Engineering Publications

This research investigated how machine operator expertise, strategies, and decision-making can be integrated into operator models that simulate authentic human behavior in construction machine operations. Physical prototype tests of construction machines require significant time and cost. However, computer-based simulation is often limited by the fidelity in which human operators are modeled. A greater understanding of how highly skilled operators obtain high machine performance and productivity can inform machine development and advance construction automation technology. Operator interviews were conducted to build a framework of tasks, strategies, and cues commonly used while controlling an excavator through repeating work cycles. A closed loop ...


A Bayesian-Influence Model For Error Probability Analysis Of Combine Operations In Harvesting, Yu Du, Michael C. Dorneich, Brian L. Steward, Cameron A. Mackenzie Sep 2016

A Bayesian-Influence Model For Error Probability Analysis Of Combine Operations In Harvesting, Yu Du, Michael C. Dorneich, Brian L. Steward, Cameron A. Mackenzie

Industrial and Manufacturing Systems Engineering Publications

Harvesting is one of the most important agricultural operations because it captures the value from the entire cropping season. In modern agriculture, grain harvesting has been mechanized through the combine harvester. A combine harvester enables highly productive crop harvesting. Combine harvesting performance depends on the highly variable skill of combine operators and associated operator error. An approach was developed to analyze the risk of the combine harvesting operation as it relates to operator error. Specifically, a risk analysis model was built based on a task analysis from operator interviews and estimates of the probability of operator error. This paper employs ...


Iteration Complexity Analysis Of Block Coordinate Descent Methods, Mingyi Hong, Xiangfeng Wang, Mesiam Razaviyayn, Zhi-Quan Luo Aug 2016

Iteration Complexity Analysis Of Block Coordinate Descent Methods, Mingyi Hong, Xiangfeng Wang, Mesiam Razaviyayn, Zhi-Quan Luo

Industrial and Manufacturing Systems Engineering Publications

In this paper, we provide a unified iteration complexity analysis for a family of general block coordinate descent methods, covering popular methods such as the block coordinate gradient descent and the block coordinate proximal gradient, under various different coordinate update rules. We unify these algorithms under the so-called block successive upper-bound minimization (BSUM) framework, and show that for a broad class of multi-block nonsmooth convex problems, all algorithms covered by the BSUM framework achieve a global sublinear iteration complexity of O(1/r)" role="presentation" style="box-sizing: border-box; display: inline-table; line-height: normal; letter-spacing: normal; word-spacing: normal; word-wrap: normal; white-space: nowrap ...


On The Linear Convergence Of The Alternating Direction Method Of Multipliers, Mingyi Hong, Zhi-Quan Luo Jul 2016

On The Linear Convergence Of The Alternating Direction Method Of Multipliers, Mingyi Hong, Zhi-Quan Luo

Industrial and Manufacturing Systems Engineering Publications

We analyze the convergence rate of the alternating direction method of multipliers (ADMM) for minimizing the sum of two or more nonsmooth convex separable functions subject to linear constraints. Previous analysis of the ADMM typically assumes that the objective function is the sum of only two convex functions defined on two separable blocks of variables even though the algorithm works well in numerical experiments for three or more blocks. Moreover, there has been no rate of convergence analysis for the ADMM without strong convexity in the objective function. In this paper we establish the global R-linear convergence of the ADMM ...


Critical Life-Cycle Decision Making For Projects Under Uncertainty, Kyung J. Min, John K. Jackman, Michelle Zugg Jun 2016

Critical Life-Cycle Decision Making For Projects Under Uncertainty, Kyung J. Min, John K. Jackman, Michelle Zugg

Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters

In this paper, we first describe how critical life-cycle decisions are made for projects facing significant uncertainties. The key differentiating aspect of our approach from the traditional net present value approach is regarding the timing of such decisions. For example, our emphasis is on the effective dates for the commencement and expiration (i.e., a window of opportunity) for possible actions regarding a project, which is clearly above and beyond a single shot decision of investment or no investment. Our approach is based on elementary stochastic optimal control methods, which often afford closed-form solutions on critical timing information such as ...


Day-Ahead Hourly Electricity Load Modeling By Functional Regression, Yonghan Feng, Sarah M. Ryan May 2016

Day-Ahead Hourly Electricity Load Modeling By Functional Regression, Yonghan Feng, Sarah M. Ryan

Industrial and Manufacturing Systems Engineering Publications

Short-term load forecasting is important for power system generation planning and operation. For unit commitment and dispatch processes to incorporate uncertainty, a short-term load model must not only provide accurate load predictions but also enable the generation of reasonable probabilistic scenarios or uncertainty sets. This paper proposes a temporal and weather conditional epi-splines based load model (TWE) using functional approximation. TWE models the dependence of load on time and weather separately by functional approximation using epi-splines, conditional on season and area, in each segment of similar weather days. Load data are transformed from various day types to a specified reference ...


Statistical Metrics For Assessing The Quality Of Wind Power Scenarios For Stochastic Unit Commitment, Didem Sari, Youngrok Lee, Sarah M. Ryan, David L. Woodruff May 2016

Statistical Metrics For Assessing The Quality Of Wind Power Scenarios For Stochastic Unit Commitment, Didem Sari, Youngrok Lee, Sarah M. Ryan, David L. Woodruff

Industrial and Manufacturing Systems Engineering Publications

In power systems with high penetration of wind generation, probabilistic scenarios are generated for use in stochastic formulations of day-ahead unit commitment problems. To minimize the expected cost, the wind power scenarios should accurately represent the stochastic process for available wind power. We employ some statistical evaluation metrics to assess whether the scenario set possesses desirable properties that are expected to lead to a lower cost in stochastic unit commitment. A new mass transportation distance rank histogram is developed for assessing the reliability of unequally likely scenarios. Energy scores, rank histograms and Brier scores are applied to alternative sets of ...


Obtaining Lower Bounds From The Progressive Hedging Algorithm For Stochastic Mixed-Integer Programs, Dinakar Gade, Gabriel Hackebeil, Sarah M. Ryan, Jean-Paul Watson, Roger J-B Wets, David L. Woodruff May 2016

Obtaining Lower Bounds From The Progressive Hedging Algorithm For Stochastic Mixed-Integer Programs, Dinakar Gade, Gabriel Hackebeil, Sarah M. Ryan, Jean-Paul Watson, Roger J-B Wets, David L. Woodruff

Industrial and Manufacturing Systems Engineering Publications

We present a method for computing lower bounds in the progressive hedging algorithm (PHA) for two-stage and multi-stage stochastic mixed-integer programs. Computing lower bounds in the PHA allows one to assess the quality of the solutions generated by the algorithm contemporaneously. The lower bounds can be computed in any iteration of the algorithm by using dual prices that are calculated during execution of the standard PHA. We report computational results on stochastic unit commitment and stochastic server location problem instances, and explore the relationship between key PHA parameters and the quality of the resulting lower bounds.


Alternating Direction Method Of Multipliers For Penalized Zero-Variance Discriminant Analysis, Brendan P.W. Ames, Mingyi Hong Feb 2016

Alternating Direction Method Of Multipliers For Penalized Zero-Variance Discriminant Analysis, Brendan P.W. Ames, Mingyi Hong

Industrial and Manufacturing Systems Engineering Publications

We consider the task of classification in the high dimensional setting where the number of features of the given data is significantly greater than the number of observations. To accomplish this task, we propose a heuristic, called sparse zero-variance discriminant analysis, for simultaneously performing linear discriminant analysis and feature selection on high dimensional data. This method combines classical zero-variance discriminant analysis, where discriminant vectors are identified in the null space of the sample within-class covariance matrix, with penalization applied to induce sparse structures in the resulting vectors. To approximately solve the resulting nonconvex problem, we develop a simple algorithm based ...


Decomposition By Successive Convex Approximation: A Unifying Approach For Linear Transceiver Design In Heterogeneous Networks, Mingyi Hong, Qiang Li, Ya-Feng Liu Feb 2016

Decomposition By Successive Convex Approximation: A Unifying Approach For Linear Transceiver Design In Heterogeneous Networks, Mingyi Hong, Qiang Li, Ya-Feng Liu

Industrial and Manufacturing Systems Engineering Publications

No abstract provided.


Hybrid Robust And Stochastic Optimization For Closed-Loop Supply Chain Network Design Using Accelerated Benders Decomposition, Esmaeil Keyvanshokooh, Sarah M. Ryan, Elnaz Kabir Feb 2016

Hybrid Robust And Stochastic Optimization For Closed-Loop Supply Chain Network Design Using Accelerated Benders Decomposition, Esmaeil Keyvanshokooh, Sarah M. Ryan, Elnaz Kabir

Industrial and Manufacturing Systems Engineering Publications

Environmental, social and economic concerns motivate the operation of closed-loop supply chain networks (CLSCN) in many industries. We propose a novel profit maximization model for CLSCN design as a mixed-integer linear program in which there is flexibility in covering the proportions of demand satisfied and returns collected based on the firm's policies. Our major contribution is to develop a novel hybrid robust-stochastic programming (HRSP) approach to simultaneously model two different types of uncertainties by including stochastic scenarios for transportation costs and polyhedral uncertainty sets for demands and returns. Transportation cost scenarios are generated using a Latin Hypercube Sampling method ...


Analysis Of Food Hub Commerce And Participation Using Agent-Based Modeling: Integrating Financial And Social Drivers, Caroline C. Krejci, Richard Stone, Michael Dorneich, Stephen B. Gilbert Feb 2016

Analysis Of Food Hub Commerce And Participation Using Agent-Based Modeling: Integrating Financial And Social Drivers, Caroline C. Krejci, Richard Stone, Michael Dorneich, Stephen B. Gilbert

Industrial and Manufacturing Systems Engineering Publications

Objective: Factors influencing long-term viability of an intermediated regional food supply network (food hub) were modeled using agent-based modeling techniques informed by interview data gathered from food hub participants.

Background: Previous analyses of food hub dynamics focused primarily on financial drivers rather than social factors and have not used mathematical models.

Method: Based on qualitative and quantitative data gathered from 22 customers and 11 vendors at a midwestern food hub, an agent-based model (ABM) was created with distinct consumer personas characterizing the range of consumer priorities. A comparison study determined if the ABM behaved differently than a model based on ...


Nestt: A Nonconvex Primal-Dual Splitting Method For Distributed And Stochastic Optimization, Davood Hajinezhad, Mingyi Hong, Tuo Zhao, Zhaoran Wang Jan 2016

Nestt: A Nonconvex Primal-Dual Splitting Method For Distributed And Stochastic Optimization, Davood Hajinezhad, Mingyi Hong, Tuo Zhao, Zhaoran Wang

Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters

We study a stochastic and distributed algorithm for nonconvex problems whose objective consists a sum N/ nonconvex Li/N/ smooth functions, plus a nonsmooth regularizer. The proposed NonconvEx primal-dual SpliTTing (NESTT) algorithm splits the problem into N/ subproblems, and utilizes an augmented Lagrangian based primal-dual scheme to solve it in a distributed and stochastic manner. With a special non-uniform sampling, a version of NESTT achieves e-1 stationary solution using...gradient evaluations, which can be up to O(N)/ times better than the (proximal) gradient descent methods. It also achieves Q-linear convergence rate for nonconvex l1 penalized quadratic problems with polyhedral ...


An Improved Convergence Analysis Of Cyclic Block Coordinate Descent-Type Methods For Strongly Convex Minimization, Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong Jan 2016

An Improved Convergence Analysis Of Cyclic Block Coordinate Descent-Type Methods For Strongly Convex Minimization, Xingguo Li, Tuo Zhao, Raman Arora, Han Liu, Mingyi Hong

Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters

The cyclic block coordinate descent-type (CBCD-type) methods have shown remarkable computational performance for solving strongly convex minimization problems. Typical applications include many popular statistical machine learning methods such as elastic-net regression, ridge penalized logistic regression, and sparse additive regression. Existing optimization literature has shown that the CBCD-type methods attain iteration complexity of O(p · log(1/e)), where e is a pre-specified accuracy of the objective value, and p is the number of blocks. However, such iteration complexity explicitly depends on p, and therefore is at least p times worse than those of gradient descent methods. To bridge this theoretical ...


Evaluating The Value Of Dynamic Terrain Simulation On Training Quality, Stephen B. Gilbert, Nir Keren, Eliot H. Winer, Warren D. Franke, Kevin Godby, Anastacia Macallister, Chloe Mcpherson, Julio De La Cruz, Applied Research Associates Jan 2016

Evaluating The Value Of Dynamic Terrain Simulation On Training Quality, Stephen B. Gilbert, Nir Keren, Eliot H. Winer, Warren D. Franke, Kevin Godby, Anastacia Macallister, Chloe Mcpherson, Julio De La Cruz, Applied Research Associates

Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters

Warfighters perform a variety of civilian duties, such as construction. For example, in Iraq, from 2004-2011, the US Army carried out over 5,000 construction projects. Training warfighters on heavy construction equipment is a timeconsuming task that contrasts with shrinking military budgets. Simulation-based training offers improved training for fewer resources. Simulators can decrease time to task proficiency by up to 90%.

Identifying the pertinent features needed for a construction equipment trainer is challenging. For example, a critical skill is identifying different soil types. Lifting too much soil can damage equipment while not taking enough can cause significant delays. An experimental ...


Quantized Consensus Admm For Multi-Agent Distributed Optimization, Shengyu Zhu, Mingyi Hong, Biao Chen Jan 2016

Quantized Consensus Admm For Multi-Agent Distributed Optimization, Shengyu Zhu, Mingyi Hong, Biao Chen

Industrial and Manufacturing Systems Engineering Conference Proceedings and Posters

Abstract: This paper considers multi-agent distributed optimization with quantized communication which is needed when inter-agent communications are subject to finite capacity and other practical constraints. To minimize the global objective formed by a sum of local convex functions, we develop a quantized distributed algorithm based on the alternating direction method of multipliers (ADMM). Under certain convexity assumptions, it is shown that the proposed algorithm converges to a consensus within log1+η Ω iterations, where η > 0 depends on the network topology and the local objectives, and O is a polynomial fraction depending on the quantization resolution, the distance between initial ...


Asynchronous Distributed Admm For Large-Scale Optimization—Part Ii: Linear Convergence Analysis And Numerical Performance, Tsung-Hui Chang, Wei-Cheng Lao, Mingyi Hong, Xiangfeng Wang Jan 2016

Asynchronous Distributed Admm For Large-Scale Optimization—Part Ii: Linear Convergence Analysis And Numerical Performance, Tsung-Hui Chang, Wei-Cheng Lao, Mingyi Hong, Xiangfeng Wang

Industrial and Manufacturing Systems Engineering Publications

The alternating direction method of multipliers (ADMM) has been recognized as a versatile approach for solving modern large-scale machine learning and signal processing problems efficiently. When the data size and/or the problem dimension is large, a distributed version of ADMM can be used, which is capable of distributing the computation load and the data set to a network of computing nodes. Unfortunately, a direct synchronous implementation of such algorithm does not scale well with the problem size, as the algorithm speed is limited by the slowest computing nodes. To address this issue, in a companion paper, we have proposed ...


Sinr Constrained Beamforming For A Mimo Multi-User Downlink System: Algorithms And Convergence Analysis, Oingjang Shi, Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo Jan 2016

Sinr Constrained Beamforming For A Mimo Multi-User Downlink System: Algorithms And Convergence Analysis, Oingjang Shi, Meisam Razaviyayn, Mingyi Hong, Zhi-Quan Luo

Industrial and Manufacturing Systems Engineering Publications

Consider a multiple-input multiple-output (MIMO) downlink multi-user channel. A well-studied problem in such a system is the design of linear beamformers for power minimization with the quality of service (QoS) constraints. The most representative algorithms for solving this class of problems are the so-called minimum mean square error (MMSE)-second-order cone programming (SOCP) algorithm [Visotksy and Madhow, “Optimum Beamforming Using Transmit Antenna Arrays,” Proc. IEEE Veh. Technol. Conf., May 1999, vol. 1, pp. 851-856] , [Wong, Zheng, and Ng, “Convergence Analysis of Downlink MIMO Antenna System Using Second-Order Cone Programming,” Proc. 62nd IEEE Veh. Technol. Conf., Sep. 2005, pp. 492-496] and ...


Modern Measurement, Probability, And Statistics: Some Generalities And Multivariate Illustrations, Stephen B. Vardeman Jan 2016

Modern Measurement, Probability, And Statistics: Some Generalities And Multivariate Illustrations, Stephen B. Vardeman

Industrial and Manufacturing Systems Engineering Publications

In broad terms, effective probability modeling of modern measurement requires the development of (usually parametric) distributions for increasingly complex multivariate outcomes driven by the physical realities of particular measurement technologies. “Differences” between measures of distribution center and truth function as “bias.” Model features that allow hierarchical compounding of variation function to describe “variance components” like “repeatability,” “reproducibility,” “batch-to-batch variation,” etc. Mixture features in models allow for description (and subsequent downweighting) of outliers. For a variety of reasons (including high-dimensionality of parameter spaces relative to typical sample sizes, the ability to directly include “Type B” considerations in assessing uncertainty, and the ...


Improving Risk Assessment Communication, Mark A. Gallagher, Cameron A. Mackenzie, David M. Blum, Douglas A. Boerman Jan 2016

Improving Risk Assessment Communication, Mark A. Gallagher, Cameron A. Mackenzie, David M. Blum, Douglas A. Boerman

Industrial and Manufacturing Systems Engineering Publications

Assessors often diminish communicating risk to show a single category or color without providing a full context of the evaluation, basis, and assumptions behind the risk assessment. We attempt to remedy that by presenting an approach to communicate risk assessments more completely with a clearer understanding of these issues. First, we specify assessor should present necessary information as part of a standard risk assessment statement. This information is discussed in four groups: 1) the activity or a collection of activities being assessed, 2) the context of the assessment (who made it, when, with what scope, and how rigorously), 3) setting ...


Modeling Disruption In A Fresh Produce Supply Chain, Cameron A. Mackenzie, Aruna Apte Jan 2016

Modeling Disruption In A Fresh Produce Supply Chain, Cameron A. Mackenzie, Aruna Apte

Industrial and Manufacturing Systems Engineering Publications

Purpose—The purpose of this paper is to quantify elements that make fresh produce supply chains vulnerable to disruptions and to quantify the benefits of different disruption management strategies.

Design/methodology/approach—This paper develops a mathematical model of a disruption in a fresh produce supply chain and analyzes the relationships among variables.

Findings—The model determines the optimal safety stock as a function of the perishability of the produce, the length of time it takes to find the contamination, the level of demand during the disruption, and the amount of produce that can be rerouted. Applying the model to ...


Sample Approximation-Based Deflation Approaches For Chance Sinr-Constrained Joint Power And Admission Control, Ya-Feng Liu, Mingyi Hong, Enbin Song Jan 2016

Sample Approximation-Based Deflation Approaches For Chance Sinr-Constrained Joint Power And Admission Control, Ya-Feng Liu, Mingyi Hong, Enbin Song

Industrial and Manufacturing Systems Engineering Publications

Consider the joint power and admission control (JPAC) problem for a multiuser single-input single-output (SISO) interference channel. Most existing works on JPAC assume the perfect instantaneous channel state information (CSI). In this paper, we consider the JPAC problem with the imperfect CSI, i.e., we assume that only the channel distribution information (CDI) is available. We formulate the JPAC problem into a chance (probabilistic)-constrained program, where each link's SINR outage probability is enforced to be less than or equal to a specified tolerance. To circumvent the computational difficulty of the chance SINR constraints, we propose to use the ...


Asynchronous Distributed Admm For Large-Scale Optimization—Part I: Algorithm And Convergence Analysis, Tsung-Hui Chang, Mingyi Hong, Wei-Cheng Liao, Xiangfeng Wang Jan 2016

Asynchronous Distributed Admm For Large-Scale Optimization—Part I: Algorithm And Convergence Analysis, Tsung-Hui Chang, Mingyi Hong, Wei-Cheng Liao, Xiangfeng Wang

Industrial and Manufacturing Systems Engineering Publications

Aiming at solving large-scale optimization problems, this paper studies distributed optimization methods based on the alternating direction method of multipliers (ADMM). By formulating the optimization problem as a consensus problem, the ADMM can be used to solve the consensus problem in a fully parallel fashion over a computer network with a star topology. However, traditional synchronized computation does not scale well with the problem size, as the speed of the algorithm is limited by the slowest workers. This is particularly true in a heterogeneous network where the computing nodes experience different computation and communication delays. In this paper, we propose ...


A Unified Algorithmic Framework For Block-Structured Optimization Involving Big Data: With Applications In Machine Learning And Signal Processing, Mingyi Hong, Meisam Razaviyayn, Zhi-Quan Luo Jan 2016

A Unified Algorithmic Framework For Block-Structured Optimization Involving Big Data: With Applications In Machine Learning And Signal Processing, Mingyi Hong, Meisam Razaviyayn, Zhi-Quan Luo

Industrial and Manufacturing Systems Engineering Publications

This article presents a powerful algorithmic framework for big data optimization, called the block successive upper-bound minimization (BSUM). The BSUM includes as special cases many well-known methods for analyzing massive data sets, such as the block coordinate descent (BCD) method, the convex-concave procedure (CCCP) method, the block coordinate proximal gradient (BCPG) method, the nonnegative matrix factorization (NMF) method, the expectation maximization (EM) method, etc. In this article, various features and properties of the BSUM are discussed from the viewpoint of design flexibility, computational efficiency, parallel/distributed implementation, and the required communication overhead. Illustrative examples from networking, signal processing, and machine ...


Joint Source-Relay Design For Full-Duplex Mimo Af Relay Systems, Qingjiang Shi, Mingyi Hong, Xiqi Gao, Enbin Song, Yunlong Cai, Weiqiang Xu Jan 2016

Joint Source-Relay Design For Full-Duplex Mimo Af Relay Systems, Qingjiang Shi, Mingyi Hong, Xiqi Gao, Enbin Song, Yunlong Cai, Weiqiang Xu

Industrial and Manufacturing Systems Engineering Publications

The performance of full-duplex (FD) relay systems can be greatly impacted by the self-interference (SI) at relays. By exploiting multiple antennas, the spectral efficiency of FD relay systems can be enhanced through spatial SI mitigation. This paper studies joint source transmit beamforming and relay processing to achieve rate maximization for FD multiple-input-multiple-output (MIMO) amplify-and-forward (AF) relay systems with consideration of relay processing delay. The problem is difficult to solve mainly due to the SI constraint induced by the relay processing delay. In this paper, we first present a sufficient condition under which the relay amplification matrix has rank-one structure. Then ...


Convergence Analysis Of Alternating Direction Method Of Multipliers For A Family Of Nonconvex Problems, Mingyi Hong, Zhi-Quan Luo, Mesiam Razaviyayn Jan 2016

Convergence Analysis Of Alternating Direction Method Of Multipliers For A Family Of Nonconvex Problems, Mingyi Hong, Zhi-Quan Luo, Mesiam Razaviyayn

Industrial and Manufacturing Systems Engineering Publications

The alternating direction method of multipliers (ADMM) is widely used to solve large-scale linearly constrained optimization problems, convex or nonconvex, in many engineering fields. However there is a general lack of theoretical understanding of the algorithm when the objective function is nonconvex. In this paper we analyze the convergence of the ADMM for solving certain nonconvex consensus and sharing problems. We show that the classical ADMM converges to the set of stationary solutions, provided that the penalty parameter in the augmented Lagrangian is chosen to be sufficiently large. For the sharing problems, we show that the ADMM is convergent regardless ...