Computer Sciences Commons^™

Approximations With Improving Error Bounds For Makespan Minimization In Batch Manufacturing, Whitney Samuel Weyerman

Theses and Dissertations

Multipurpose batch manufacturing systems allow a suite of job types to be processed with a fixed set of machines. These types of systems are commonly found in chemical processing, as well as in computer systems and the service industry. In this thesis we consider the problem of sequencing jobs entering the manufacturing system in order to minimize makespan, or total time to complete processing of the jobs. We formulate this problem as a dynamic programming problem and illustrate the computational difficulty of solving this problem. We give a method for simulation of the system by representing each machine in the …

Some Combinational Optimization Problems On Radio Network Communication And Machine Scheduling, Xin Wang

Dissertations

The combinatorial optimization problems coming from two areas are studied in this dissertation: network communication and machine scheduling.

In the network communication area, the complexity of distributed broadcasting and distributed gossiping is studied in the setting of random networks. Two different models are considered: one is random geometric networks, the main model used to study properties of sensor and ad-hoc networks, where ri points are randomly placed in a unit square and two points are connected by an edge if they are at most a certain fixed distance r from each other. The other model is the so-called line-of-sight networks, …

Evolutionary Methodology For Optimization Of Image Transforms Subject To Quantization Noise, Michael Ray Peterson

Browse all Theses and Dissertations

Lossy image compression algorithms sacrifice perfect imagereconstruction in favor of decreased storage requirements. Modelossy compression schemes, such as JPEG2000, rely upon the discrete wavelet transform (DWT) to achieve high levels of compression while minimizing the loss of information for image reconstruction. Some compression applications require higher levels of compression than those achieved through application of the DWT and entropy coding. In such lossy systems, quantization provides high compression rates at the cost of increased distortion. Unfortunately, as the amount of quantization increases, the performance of the DWT for accurate image reconstruction deteriorates. Previous research demonstrates that a genetic algorithm can …

Analysis And Optimization Of Mobile Phone Antenna Radiation Performance In The Presence Of Head And Hand Phantoms, Erdem Ofli, Chung-Huan Li, Nicolas Chavannes, Niels Kuster

Turkish Journal of Electrical Engineering and Computer Sciences

A commercial clam shell phone CAD model is used to numerically investigate the effect of a hand phantom on mobile phone antenna radiation performance. The simulation results show that the grip of the hand phantom is the most important parameter to antenna performance. The antenna is converted into a parameterized form, then optimized to achieve the targeted multi-band performance in real-usage conditions.

Model-Driven Search-Based Loop Fusion Optimization For Handwritten Code, Pamela Bhattacharya

LSU Master's Theses

The Tensor Contraction Engine (TCE) is a compiler that translates high-level, mathematical tensor contraction expressions into efficient, parallel Fortran code. A pair of optimizations in the TCE, the fusion and tiling optimizations, have proven successful for minimizing disk-to-memory traffic for dense tensor computations. While other optimizations are specific to tensor contraction expressions, these two model-driven search-based optimization algorithms could also be useful for optimizing handwritten dense array computations to minimize disk to memory traffic. In this thesis, we show how to apply the loop fusion algorithm to handwritten code in a procedural language. While in the TCE the loop fusion …

Validating Pareto Optimal Operation Parameters Of Polyp Detection Algorithms For Ct Colonography, Jiang Li, Adam Huang, Nicholas Petrick, Jianhua Yao, Ronald M. Summers, Maryellen L. Giger (Ed.), Nico Karssemeijer (Ed.)

Electrical & Computer Engineering Faculty Publications

We evaluated a Pareto front-based multi-objective evolutionary algorithm for optimizing our CT colonography (CTC) computer-aided detection (CAD) system. The system identifies colonic polyps based on curvature and volumetric based features, where a set of thresholds for these features was optimized by the evolutionary algorithm. We utilized a two-fold cross-validation (CV) method to test if the optimized thresholds can be generalized to new data sets. We performed the CV method on 133 patients; each patient had a prone and a supine scan. There were 103 colonoscopically confirmed polyps resulting in 188 positive detections in CTC reading from either the prone or …

No Free Lunch, Bayesian Inference, And Utility: A Decision-Theoretic Approach To Optimization, Christopher Kenneth Monson

Theses and Dissertations

Existing approaches to continuous optimization are essentially mechanisms for deciding which locations should be sampled in order to obtain information about a target function's global optimum. These methods, while often effective in particular domains, generally base their decisions on heuristics developed in consideration of ill-defined desiderata rather than on explicitly defined goals or models of the available information that may be used to achieve them. The problem of numerical optimization is essentially one of deciding what information to gather, then using that information to infer the location of the global optimum. That being the case, it makes sense to model …

Post Register Allocation Spill Code Optimization, Christopher Lupo, Kent Wilken

Computer Science and Software Engineering

A highly optimized register allocator should provide an efficient placement of save/restore code for procedures that contain calls. This paper presents a new approach to placing callee-saved save and restore instructions that generalizes Chow's shrink-wrapping technique (Chow 1988). An efficient, profile-guided, hierarchical spill code placement algorithm is used to analyze the structure of a procedure to calculate the minimum dynamic execution count locations to place callee-saved save and restore code. The algorithm is implemented in the Gnu Compiler Collection and has been tested on the SPEC CPU2000 Integer Benchmark suite. Results show that the technique reduces the number of dynamic …

An Efficient And Robust Computational Framework For Studying Lifetime And Information Capacity In Sensor Networks, Enrique J. Duarte-Melo, Mingyan Liu, Archan Misra

Research Collection School Of Computing and Information Systems

In this paper we investigate the expected lifetime and information capacity, defined as the maximum amount of data (bits) transferred before the first sensor node death due to energy depletion, of a data-gathering wireless sensor network. We develop a fluid-flow based computational framework that extends the existing approach, which requires precise knowledge of the layout/deployment of the network, i.e., exact sensor positions. Our method, on the other hand, views a specific network deployment as a particular instance (sample path) from an underlying distribution of sensor node layouts and sensor data rates. To compute the expected information capacity under this distribution-based …

Order Scheduling In Dedicated And Flexible Machine Environments, Haibing Li

Dissertations

Order scheduling models are relatively new in the field of scheduling. Consider a facility with m parallel machines that can process k different products (job types). Each machine can process a given subset of different product types. There are n orders from n different clients. Each order requests specific quantities of the various different products that can be produced concurrently on their given subsets of machines; it may have a release date, a weight and a due date. Preemptions may be allowed. An order can not be shipped until the processing of all the products for the order has been …

Tournament Versus Fitness Uniform Selection, Shane Legg, Marcus Hutter, Akshat Kumar

Research Collection School Of Computing and Information Systems

In evolutionary algorithms a critical parameter that must be tuned is that of selection pressure. If it is set too low then the rate of convergence towards the optimum is likely to be slow. Alternatively if the selection pressure is set too high the system is likely to become stuck in a local optimum due to a loss of diversity in the population. The recent Fitness Uniform Selection Scheme (FUSS) is a conceptually simple but somewhat radical approach to addressing this problem - rather than biasing the selection towards higher fitness, FUSS biases selection towards sparsely populated fitness levels. In …

A Modeling Framework For Computing Lifetime And Information Capacity In Wireless Sensor Networks, Enrique Duarte-Melo, Mingyan Liu, Archan Misra

Research Collection School Of Computing and Information Systems

In this paper we investigate the expected lifetime and information capacity, defined as the maximum amount of data (bits) transferred before the first sensor node death due to energy depletion, of a data-gathering wireless sensor network. We develop a fluidflow based computational framework that extends the existing approach, which requires precise knowledge of the layout/deployment of the network, i.e., exact sensor positions. Our method, on the other hand, views a specific network deployment as a particular instance (sample path) from an underlying distribution of sensor node layouts and sensor data rates.

A Simple And Global Optimization Algorithm For Engineering Problems: Differential Evolution Algorithm, Dervi̇ş Karaboğa, Selçuk Ökdem

Turkish Journal of Electrical Engineering and Computer Sciences

Differential Evolution (DE) algorithm is a new heuristic approach mainly having three advantages; finding the true global minimum regardless of the initial parameter values, fast convergence, and using few control parameters. DE algorithm is a population based algorithm like genetic algorithms using similar operators; crossover, mutation and selection. In this work, we have compared the performance of DE algorithm to that of some other well known versions of genetic algorithms: PGA, Grefensstette, Eshelman. In simulation studies, De Jong's test functions have been used. From the simulation results, it was observed that the convergence speed of DE is significantly better than …

Analysis Of A Yield Management Model For On Demand Computing Centers, Yezekael Hayel, Laura Wynter, Parijat Dube

Research Collection School Of Computing and Information Systems

The concept of yield management for IT infrastructures, and in particular for on demand IT utilities was recently introduced in [17]. The present paper provides a detailed analysis of that model, both in simplified cases where an analytical analysis is possible, and numerically on larger problem instances, and confirms the significant revenue benefit that can accrue through use of yield management in an IT on demand operating environment.

The Computational Complexity Of N-K Fitness Functions, Alden H. Wright, Richard K. Thompson, Jian Zhang

Computer Science Faculty Publications

N-K fitness landscapes have been widely used as examples and test functions in the field of evolutionary computation. Thus, the computational complexity of these landscapes as optimization problems is of interest. We investigate the computational complexity of the problem of optimizing the N-K fitness functions and related fitness functions. We give an algorithm to optimize adjacent-model N-K fitness functions which is polynomial in N. We show that the decision problem corresponding to optimizing random-model N-K fitness functions is NP-complete for K > 1 and is polynomial for K = 1. If the restriction that the ith component function depends …

Rescaling The Energy Function In Hopfield Networks, Tony R. Martinez, Xinchuan Zeng

Faculty Publications

In this paper we propose an approach that rescales the distance matrix of the energy function in the Hopfield network for solving optimization problems. We rescale the distance matrix by normalizing each row in the matrix and then adjusting the parameter for the distance term. This scheme has the capability of reducing the effects of clustering in data distributions, which is one of main reasons for the formation of invalid solutions. We evaluate this approach through a large number (20,000) simulations based on 200 randomly generated city distributions of the 10-city traveling salesman problem. The result shows that, compared to …

Multiobjective Evolutionary Algorithms: Classifications, Analyses, And New Innovations, David A. Van Veldhuizen

Theses and Dissertations

This research organizes, presents, and analyzes contemporary Multiobjective Evolutionary Algorithm (MOEA) research and associated Multiobjective Optimization Problems (MOPs). Using a consistent MOEA terminology and notation, each cited MOEAs' key factors are presented in tabular form for ease of MOEA identification and selection. A detailed quantitative and qualitative MOEA analysis is presented, providing a basis for conclusions about various MOEA-related issues. The traditional notion of building blocks is extended to the MOP domain in an effort to develop more effective and efficient MOEAs. Additionally, the MOEA community's limited test suites contain various functions whose origins and rationale for use are often …

Nonrecursive Incremental Evaluation Of Datalog Queries, Guozhu Dong, Jianwen Su, Rodney Topor

Kno.e.sis Publications

We consider the problem of repeatedly evaluating the same (computationally expensive) query to a database that is being updated between successive query requests. In this situation, it should be possible to use the difference between successive database states and the answer to the query in one state to reduce the cost of evaluating the query in the next state. We use nonrecursive Datalog (which are unions of conjunctive queries) to compute the differences, and call this process “incremental query evaluation using conjunctive queries”. After formalizing the notion of incremental query evaluation using conjunctive queries, we give an algorithm that constructs, …

Linear Time Optimization Algorithms For P4-Sparse Graphs, Beverly Jamison, Stephan Olariu

Computer Science Faculty Publications

Quite often, real-life applications suggest the study of graphs that feature some local density properties. In particular, graphs that are unlikely to have more than a few chordless paths of length three appear in a number of contexts. A graph G is P₄-sparse if no set of five vertices in G induces more than one chordless path of length three. P₄-sparse graphs generalize both the class of cographs and the class of P₄-reducible graphs. It has been shown that P₄-sparse graphs can be recognized in time linear in the size of the …

Automated Manpower Rostering: Techniques And Experience, C. M. Khoong, Hoong Chuin Lau, L. W. Chew

Research Collection School Of Computing and Information Systems

We present ROMAN, a comprehensive, generic manpower rostering toolkit that successfully handles a wide spectrum of work policies found in service organizations. We review the use of various techniques and methodologies in the toolkit that contribute to its robustness and efficiency, and relate experience gained in addressing manpower rostering problems in industry.

Correction To "Redundancy Optimization Of General Systems", H. Sivaramakrishnan, Arcot Desai Narasimhalu

Research Collection School Of Computing and Information Systems

Reader Aids-

Purpose: Report a correction

Special math needed: Probability

Results useful to: Reliability Theoreticians

A Rapid Algorithm For Reliability Optimization Of Parallel Redundant Systems, Arcot Desai Narasimhalu, H. Sivaramakrishnan

Research Collection School Of Computing and Information Systems

A rapid method is proposed for optimization of reliability of multiconstraint parallel redundant systems. The constraints need not be linear. This method provides good starting values, which are close to the boundary of the feasible region, for the number of redundant units in each subsystem. No proof has been presented to establish the optimality obtained by this method. Yet for examples tried out this method provides optimal or near optimal solutions.