: 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 unknown. Thus, using general test suite guidelines appropriate MOEA test function suites are substantiated and generated. An experimental methodology incorporating a solution database and appropriate metrics is offered as a proposed evaluation framework allowing absolute comparisons of specific MOEA approaches. Taken together, this document's classifications, analyses, and new innovations present a complete, contemporary view of current MOEA "state of the art" and possible future research. Researchers with basic EA knowledge may also use part of it as a largely self-contained introduction to MOEAs.

Multiobjective evolutionary algorithms: classifications, analyses, and new innovations

From the Publisher:
This work covers all aspects of physical design. The book is a core reference for graduate students and CAD professionals. For students, concept and algorithms are presented in an intuitive manner. For CAD professionals, the material presents a balance of theory and practice. An extensive bibliography is provided which is useful for finding advanced material on a topic. At the end of each chapter, exercises are provided, which range in complexity from simple to research level.

Algorithms for VLSI Physical Design Automation

This paper is the result of a literature study carried out by the authors. It is a review of the different attempts made to solve the Travelling Salesman Problem with Genetic Algorithms. We present crossover and mutation operators, developed to tackle the Travelling Salesman Problem with Genetic Algorithms with different representations such as: binary representation, path representation, adjacency representation, ordinal representation and matrix representation. Likewise, we show the experimental results obtained with different standard examples using combination of crossover and mutation operators in relation with path representation.

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Genetic Algorithms for the Travelling Salesman Problem: A Review of Representations and Operators

Hybrid metaheuristics have received considerable interest these recent years in the field of combinatorial optimization. A wide variety of hybrid approaches have been proposed in the literature. In this paper, a taxonomy of hybrid metaheuristics is presented in an attempt to provide a common terminology and classification mechanisms. The taxonomy, while presented in terms of metaheuristics, is also applicable to most types of heuristics and exact optimization algorithms.

As an illustration of the usefulness of the taxonomy an annoted bibliography is given which classifies a large number of hybrid approaches according to the taxonomy.

A Taxonomy of Hybrid Metaheuristics

We consider a fully SAT-based method of unbounded symbolic model checking based on computing Craig interpolants. In benchmark studies using a set of large industrial circuit verification instances, this method is greatly more efficient than BDD-based symbolic model checking, and compares favorably to some recent SAT-based model checking methods on positive instances.

Interpolation and SAT-based model checking

New design flows require reducing work at the gate level and performing most activities before the synthesis step, including evaluation of testability of circuits. We propose a suite of RT-level benchmarks that help improve research in high-level ATPG tools. First results on the benchmarks obtained with our prototype tool show the feasibility of the approach.

RT-level ITC'99 benchmarks and first ATPG results

Triple modular redundancy (TMR) is a suitable fault tolerant technique for SRAM-based FPGA However, one of the main challenges in achieving 100% robustness in designs protected by TMR running on programmable platforms is to prevent upsets in the routing from provoking undesirable connections between signals from distinct redundant logic parts, which can generate an error in the output This paper investigates the optimal design of the TMR logic (eg, by cleverly inserting voters) to ensure robustness Four different versions of a TMR digital filter were analyzed by fault injection Faults were randomly inserted straight into the bitstream of the FPGA The experimental results presented in this paper demonstrate that the number and placement of voters in the TMR design can directly affect the fault tolerance, ranging from 403% to 098% the number of upsets in the routing able to cause an error in the TMR circuit

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On the Optimal Design of Triple Modular Redundancy Logic for SRAM-based FPGAs

This article discusses the potential role of software-based self-testing in the microprocessor test and validation process, as well as its supplementary role in other classic functional- and structural-test methods. In addition, the article proposes a taxonomy for different SBST methodologies according to their test program development philosophy, and summarizes research approaches based on SBST techniques for optimizing other key aspects.

Microprocessor Software-Based Self-Testing

This book presents the theory behind software-implemented hardware fault tolerance, as well as the practical aspects needed to put it to work on real examples. By evaluating accurately the advantages and disadvantages of the already available approaches, the book provides a guide to developers willing to adopt software-implemented hardware fault tolerance in their applications. Moreover, the book identifies open issues for researchers willing to improve the already available techniques.

Software-Implemented Hardware Fault Tolerance

Design validation is a critical step in the development of present-day microprocessors, and some authors suggest that up to 60% of the design cost is attributable to this activity. Of the numerous activities performed in different stages of the design flow and at different levels of abstraction, we focus on simulation-based design validation performed at the behavioral register-transfer level. Designers typically write assertions inside hardware description language (HDL) models and run extensive simulations to increase confidence in device correctness. Simulation results can also be useful in comparing the HDL model against higher-level references or instruction set simulators. Microprocessor validation has become more difficult since the adoption of pipelined architectures, mainly because you can't evaluate the behavior of a pipelined microprocessor by considering one instruction at a time; a pipeline's behavior depends on a sequence of instructions and all their operands.

Matteo Sonza Reorda

Papers

RT-level ITC'99 benchmarks and first ATPG results

On the Optimal Design of Triple Modular Redundancy Logic for SRAM-based FPGAs

Microprocessor Software-Based Self-Testing

Software-Implemented Hardware Fault Tolerance

Automatic test program generation: a case study