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

Orienteering Problem: A Survey Of Recent Variants, Solution Approaches And Applications, Aldy Gunawan, Hoong Chuin Lau, Pieter Vansteenwegen Dec 2016

Orienteering Problem: A Survey Of Recent Variants, Solution Approaches And Applications, Aldy Gunawan, Hoong Chuin Lau, Pieter Vansteenwegen

Research Collection School Of Information Systems

The Orienteering Problem (OP) has received a lot of attention in the past few decades. The OP is a routing problem in which the goal is to determine a subset of nodes to visit, and in which order, so that the total collected score is maximized and a given time budget is not exceeded. A number of typical variants has been studied, such as the Team OP, the (Team) OP with Time Windows and the Time Dependent OP. Recently, a number of new variants of the OP was introduced, such as the Stochastic OP, the Generalized OP, the Arc OP ...


Orienteering Problem: A Survey Of Recent Variants, Solution Approaches And Applications, Aldy Gunawan, Hoong Chuin Lau, Pieter Vansteenwegen Dec 2016

Orienteering Problem: A Survey Of Recent Variants, Solution Approaches And Applications, Aldy Gunawan, Hoong Chuin Lau, Pieter Vansteenwegen

Research Collection School Of Information Systems

The Orienteering Problem (OP) has received a lot of attention in the past few decades. The OP is a routing problem in which the goal is to determine a subset of nodes to visit, and in which order, so that the total collected score is maximized and a given time budget is not exceeded. A number of typical variants has been studied, such as the Team OP, the (Team) OP with Time Windows and the Time Dependent OP. Recently, a number of new variants of the OP was introduced, such as the Stochastic OP, the Generalized OP, the Arc OP ...


Managing Egress Of Crowd During Infrastructure Disruption, Teck Hou Teng, Shih-Fen Cheng, Trong-Nghia Truong, Hoong Chuin Lau Dec 2016

Managing Egress Of Crowd During Infrastructure Disruption, Teck Hou Teng, Shih-Fen Cheng, Trong-Nghia Truong, Hoong Chuin Lau

Research Collection School Of Information Systems

In a large indoor environment such as a sports arena or convention center, smooth egress of crowd after an event can be seriously affected if infrastructure such as elevators and escalators break down. In this paper, we propose a novel crowd simulator known as SIM-DISRUPT for simulating egress scenarios in non-emergency situations. To surface the impact of disrupted infrastructure on the egress of crowd, SIM-DISRUPT includes features that allow users to specify selective disruptions as well as strategies for controlling the distribution and egress choices of crowd. Using SIM-DISRUPT, we investigate effects of crowd distribution, egress choices and infrastructure disruptions ...


An Agent-Based Approach To Human Migration Movement, Larry Lin, Kathleen M. Carley, Shih-Fen Cheng Dec 2016

An Agent-Based Approach To Human Migration Movement, Larry Lin, Kathleen M. Carley, Shih-Fen Cheng

Research Collection School Of Information Systems

How are the populations of the world likely to shift? Which countries will be impacted by sea-level rise? This paper uses a country-level agent-based dynamic network model to examine shifts in population given network relations among countries, which influences overall population change. Some of the networks considered include: alliance networks, shared language networks, economic influence networks, and proximity networks. Validation of model is done for migration probabilities between countries, as well as for country populations and distributions. The proposed framework provides a way to explore the interaction between climate change and policy factors at a global scale.


Traffic Simulation Model For Port Planning And Congestion Prevention, Baoxiang Li, Kar Way Tan, Trong Khiem Tran Dec 2016

Traffic Simulation Model For Port Planning And Congestion Prevention, Baoxiang Li, Kar Way Tan, Trong Khiem Tran

Research Collection School Of Information Systems

Effective management of land-side transportation provides the competitive advantage to port terminal operators in improving services and efficient use of limited space in an urban port. We present a hybrid simulation model that combines traffic-flow modeling and discrete-event simulation for land-side port planning and evaluation of traffic conditions for a number of what-if scenarios. We design our model based on a real-world case of a bulk cargo port. The problem is interesting due to complexity of heterogeneous closed-looped internal vehicles and external vehicles traveling in spaces with very limited traffic regulation (no traffic lights, no traffic wardens) and the traffic ...


Shape Analysis Of Traffic Flow Curves Using A Hybrid Computational Analysis, Wasim Irshad Kayani, Shikhar P. Acharya, Ivan G. Guardiola, Donald C. Wunsch, B. Schumacher, Isaac Wagner-Muns Nov 2016

Shape Analysis Of Traffic Flow Curves Using A Hybrid Computational Analysis, Wasim Irshad Kayani, Shikhar P. Acharya, Ivan G. Guardiola, Donald C. Wunsch, B. Schumacher, Isaac Wagner-Muns

Engineering Management and Systems Engineering Faculty Research & Creative Works

This paper highlights and validates the use of shape analysis using Mathematical Morphology tools as a means to develop meaningful clustering of historical data. Furthermore, through clustering more appropriate grouping can be accomplished that can result in the better parameterization or estimation of models. This results in more effective prediction model development. Hence, in an effort to highlight this within the research herein, a Back-Propagation Neural Network is used to validate the classification achieved through the employment of MM tools. Specifically, the Granulometric Size Distribution (GSD) is used to achieve clustering of daily traffic flow patterns based solely on their ...


Improving Carbon Efficiency Through Container Size Optimization And Shipment Consolidation, Nang Laik Ma, Kar Way Tan, Edwin Lik Ming Chong Sep 2016

Improving Carbon Efficiency Through Container Size Optimization And Shipment Consolidation, Nang Laik Ma, Kar Way Tan, Edwin Lik Ming Chong

Research Collection School Of Information Systems

Purpose: Many manufacturing companies that ship goods through full container loads found themselves under-utilizing the containers and resulting in higher carbon footprint per volume shipment. One of the reasons is the choice of non-ideal container sizes for their shipments. Consolidation fills up the containers more efficiently that reduces the overall carbon footprint. The objective of this paper is to support decisions on selection of appropriate combination of container sizes and shipment consolidation for a manufacturing company. We develop two-steps model which first takes the volumes to be shipped as an input and provide the combination of container sizes required; then ...


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 ...


Enhancing Local Search With Adaptive Operator Ordering And Its Application To The Time Dependent Orienteering Problem, Aldy Gunawan, Hoong Chuin Lau, Kun Lu Aug 2016

Enhancing Local Search With Adaptive Operator Ordering And Its Application To The Time Dependent Orienteering Problem, Aldy Gunawan, Hoong Chuin Lau, Kun Lu

Research Collection School Of Information Systems

No abstract provided.


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 ...


Analysis Of A Parallel Machine Scheduling Problem With Sequence Dependent Setup Times And Job Availability Intervals, Ridvan Gedik, Chase Rainwater, Heather Nachtmann, Edward A. Pohl Jun 2016

Analysis Of A Parallel Machine Scheduling Problem With Sequence Dependent Setup Times And Job Availability Intervals, Ridvan Gedik, Chase Rainwater, Heather Nachtmann, Edward A. Pohl

Mechanical and Industrial Engineering Faculty Publications

In this study, we propose constraint programming (CP) model and logic-based Benders algorithms in order to make the best decisions for scheduling non-identical jobs with availability intervals and sequence dependent setup times on unrelated parallel machines in a fixed planning horizon. In this problem, each job has a profit, cost and must be assigned to at most one machine in such a way that total profit is maximized. In addition, the total cost has to be less than or equal to a budget level. Computational tests are performed on a real-life case study prepared in collaboration with the U.S ...


Designing And Comparing Multiple Portfolios Of Parameter Configurations For Online Algorithm Selection, Aldy Gunawan, Hoong Chuin Lau, Mustafa Misir Jun 2016

Designing And Comparing Multiple Portfolios Of Parameter Configurations For Online Algorithm Selection, Aldy Gunawan, Hoong Chuin Lau, Mustafa Misir

Research Collection School Of Information Systems

Algorithm portfolios seek to determine an effective set of algorithms that can be used within an algorithm selection framework to solve problems. A limited number of these portfolio studies focus on generating different versions of a target algorithm using different parameter configurations. In this paper, we employ a Design of Experiments (DOE) approach to determine a promising range of values for each parameter of an algorithm. These ranges are further processed to determine a portfolio of parameter configurations, which would be used within two online Algorithm Selection approaches for solving different instances of a given combinatorial optimization problem effectively. We ...


Strategic Planning For Setting Up Base Stations In Emergency Medical Systems, Supriyo Ghosh, Pradeep Varakantham Jun 2016

Strategic Planning For Setting Up Base Stations In Emergency Medical Systems, Supriyo Ghosh, Pradeep Varakantham

Research Collection School Of Information Systems

Emergency Medical Systems (EMSs) are an important component of public health-care services. Improving infrastructure for EMS and specifically the construction of base stations at the ”right” locations to reduce response times is the main focus of this paper. This is a computationally challenging task because of the: (a) exponentially large action space arising from having to consider combinations of potential base locations, which themselves can be significant; and (b) direct impact on the performance of the ambulance allocation problem, where we decide allocation of ambulances to bases. We present an incremental greedy approach to discover the placement of bases that ...


Dual Formulations For Optimizing Dec-Pomdp Controllers, Akshat Kumar, Hala Mostafa, Shlomo Zilberstein Jun 2016

Dual Formulations For Optimizing Dec-Pomdp Controllers, Akshat Kumar, Hala Mostafa, Shlomo Zilberstein

Research Collection School Of Information Systems

Decentralized POMDP is an expressive model for multi-agent planning. Finite-state controllers (FSCs)---often used to represent policies for infinite-horizon problems---offer a compact, simple-to-execute policy representation. We exploit novel connections between optimizing decentralized FSCs and the dual linear program for MDPs. Consequently, we describe a dual mixed integer linear program (MIP) for optimizing deterministic FSCs. We exploit the Dec-POMDP structure to devise a compact MIP and formulate constraints that result in policies executable in partially-observable decentralized settings. We show analytically that the dual formulation can also be exploited within the expectation maximization (EM) framework to optimize stochastic FSCs. The resulting EM ...


Self-Organizing Neural Network For Adaptive Operator Selection In Evolutionary Search, Teck Hou Teng, Stephanus Daniel Handoko, Hoong Chuin Lau Jun 2016

Self-Organizing Neural Network For Adaptive Operator Selection In Evolutionary Search, Teck Hou Teng, Stephanus Daniel Handoko, Hoong Chuin Lau

Research Collection School Of Information Systems

Evolutionary Algorithm is a well-known meta-heuristics paradigm capable of providing high-quality solutions to computationally hard problems. As with the other meta-heuristics, its performance is often attributed to appropriate design choices such as the choice of crossover operators and some other parameters. In this chapter, we propose a continuous state Markov Decision Process model to select crossover operators based on the states during evolutionary search. We propose to find the operator selection policy efficiently using a self-organizing neural network, which is trained offline using randomly selected training samples. The trained neural network is then verified on test instances not used for ...


Simultaneous Optimization And Sampling Of Agent Trajectories Over A Network, Hala Mostafa, Akshat Kumar, Hoong Chuin Lau May 2016

Simultaneous Optimization And Sampling Of Agent Trajectories Over A Network, Hala Mostafa, Akshat Kumar, Hoong Chuin Lau

Research Collection School Of Information Systems

We study the problem of optimizing the trajectories of agents moving over a network given their preferences over which nodes to visit subject to operational constraints on the network. In our running example, a theme park manager optimizes which attractions to include in a day-pass to maximize the pass’s appeal to visitors while keeping operational costs within budget. The first challenge in this combinatorial optimization problem is that it involves quantities (expected visit frequencies of each attraction) that cannot be expressed analytically, for which we use the Sample Average Approximation. The second challenge is that while sampling is typically ...


Reinforcement Learning Framework For Modeling Spatial Sequential Decisions Under Uncertainty: (Extended Abstract), Truc Viet Le, Siyuan Liu, Hoong Chuin Lau May 2016

Reinforcement Learning Framework For Modeling Spatial Sequential Decisions Under Uncertainty: (Extended Abstract), Truc Viet Le, Siyuan Liu, Hoong Chuin Lau

Research Collection School Of Information Systems

We consider the problem of trajectory prediction, where a trajectory is an ordered sequence of location visits and corresponding timestamps. The problem arises when an agent makes sequential decisions to visit a set of spatial locations of interest. Each location bears a stochastic utility and the agent has a limited budget to spend. Given the agent's observed partial trajectory, our goal is to predict the remaining trajectory. We propose a solution framework to the problem considering both the uncertainty of utility and the budget constraint. We use reinforcement learning (RL) to model the underlying decision processes and inverse RL ...


Robust Influence Maximization, Meghna Lowalekar, Pradeep Varakantham, Akshat Kumar May 2016

Robust Influence Maximization, Meghna Lowalekar, Pradeep Varakantham, Akshat Kumar

Research Collection School Of Information Systems

Influence Maximization is the problem of finding a fixed size set of nodes, which will maximize the expected number of influenced nodes in a social network. The number of influenced nodes is dependent on the influence strength of edges that can be very noisy. The noise in the influence strengths can be modeled using a random noise or adversarial noise model. It has been shown that all random processes that independently affect edges of the graph can be absorbed into the activation probabilities themselves and hence random noise can be captured within the independent cascade model. On the other hand ...


In The Face Of Anticipation: Decision Making Under Visible Uncertainty As Present In The Safest-With-Sight Problem, Bryan A. Knowles Apr 2016

In The Face Of Anticipation: Decision Making Under Visible Uncertainty As Present In The Safest-With-Sight Problem, Bryan A. Knowles

Masters Theses & Specialist Projects

Pathfinding, as a process of selecting a fixed route, has long been studied in

Computer Science and Mathematics. Decision making, as a similar, but intrinsically different, process of determining a control policy, is much less studied. Here, I propose a problem that appears to be of the first class, which would suggest that it is easily solvable with a modern machine, but that would be too easy, it turns out. By allowing a pathfinding to anticipate and respond to information, without setting restrictions

on the \structure" of this anticipation, selecting the \best step" appears to be an intractable problem.

After ...


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.


Shortest Path Based Decision Making Using Probabilistic Inference, Akshat Kumar Feb 2016

Shortest Path Based Decision Making Using Probabilistic Inference, Akshat Kumar

Research Collection School Of Information Systems

We present a new perspective on the classical shortest path routing (SPR) problem in graphs. We show that the SPR problem can be recast to that of probabilistic inference in a mixture of simple Bayesian networks. Maximizing the likelihood in this mixture becomes equivalent to solving the SPR problem. We develop the well known Expectation-Maximization (EM) algorithm for the SPR problem that maximizes the likelihood, and show that it does not get stuck in a locally optimal solution. Using the same probabilistic framework, we then address an NP-Hard network design problem where the goal is to repair a network of ...


An Efficient Solution To The Mixed Shop Scheduling Problem Using A Modified Genetic Algorithm, V. Nguyen, H. P. Bao Jan 2016

An Efficient Solution To The Mixed Shop Scheduling Problem Using A Modified Genetic Algorithm, V. Nguyen, H. P. Bao

Mechanical & Aerospace Engineering Faculty Publications

The mixed job shop scheduling problem is one in which some jobs have fixed machine orders and other jobs may be processed in arbitrary orders. In past literature, optimal solutions have been proposed based on adaptations of classical solutions such as by Johnson, Thompson and Giffler among many others, by pseudopolynomial algorithms, by simulation, and by Genetic Algorithms (GA). GA based solutions have been proposed for flexible Job shops. This paper proposes a GA algorithm for the mixed job shop scheduling problem. The paper starts with an analysis of the characteristics of the so-called mixed shop problem. Based on those ...


The Reconfigurable Machinery Efficient Workspace Analysis Based On The Twist Angles, Ana M. Djuric, Vukica Jovanovic, Mirjana Filipovic, Ljubinko Kevac Jan 2016

The Reconfigurable Machinery Efficient Workspace Analysis Based On The Twist Angles, Ana M. Djuric, Vukica Jovanovic, Mirjana Filipovic, Ljubinko Kevac

Engineering Technology Faculty Publications

A novel methodology for the calculation, visualisation and analysis of the Reconfigurable Machinery Efficient Workspace (RMEW), based on the twist angles, is presented in this paper. The machinery's kinematic parameters are used for calculating the workspace, while the efficient workspace is associated with the machinery's path and includes the end-effector position and orientation. To analyse and visualise many different machinery efficient workspaces at the same time, the calculation is based on the previously developed and validated complex reconfigurable machinery's kinematic structure named n-DOF Global Kinematic Model (n-GKM). An industrial robot is used as an example ...


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 ...


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 ...


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 ...


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 ...


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 ...