Task scheduling in VLSI circuit design: algorithm and bounds.

• Other Authors: Lam, Shiu-chung.
• Format: Others
• Language: English; Chinese
• Published: 1999
• Subjects: Production scheduling > Mathematical models; Integrated circuits > Very large scale integration > Design; Genetic algorithms
• Online Access: http://library.cuhk.edu.hk/record=b5890147; http://repository.lib.cuhk.edu.hk/en/item/cuhk-322912

by Lam Shiu-chung. === Thesis (M.Phil.)--Chinese University of Hong Kong, 1999. === Includes bibliographical references (leaves 107-113). === Abstracts in English and Chinese. === List of Figures --- p.v === List of Tables --- p.vii === Chapter 1 --- Introduction --- p.1 === Chapter 1.1 --- Motivation --- p.1 === Chapter 1.2 --- Task Scheduling Problem and Lower Bound --- p.3 === Chapter 1.3 --- Organization of the Thesis --- p.4 === Chapter 2 --- Teamwork-Task Scheduling Problem --- p.5 === Chapter 2.1 --- Problem Statement and Notations --- p.5 === Chapter 2.2 --- Classification of Scheduling --- p.7 === Chapter 2.3 --- Computational Complexity --- p.9 === Chapter 2.4 --- Literature Review --- p.12 === Chapter 2.4.1 --- Unrelated Machines Scheduling Environment --- p.12 === Chapter 2.4.2 --- Multiprocessors Scheduling Problem --- p.13 === Chapter 2.4.3 --- Search Algorithms --- p.14 === Chapter 2.4.4 --- Lower Bounds --- p.15 === Chapter 2.5 --- Summary --- p.17 === Chapter 3 --- Fundamentals of Genetic Algorithms --- p.18 === Chapter 3.1 --- Initial Inspiration --- p.18 === Chapter 3.2 --- An Elementary Genetic Algorithm --- p.20 === Chapter 3.2.1 --- "Genes, Chromosomes and Representations" --- p.20 === Chapter 3.2.2 --- Population Pool --- p.22 === Chapter 3.2.3 --- Evaluation Module --- p.22 === Chapter 3.2.4 --- Reproduction Module --- p.22 === Chapter 3.2.5 --- Genetic Operators: Crossover and Mutation --- p.23 === Chapter 3.2.6 --- Parameters --- p.24 === Chapter 3.3 --- A Brief Note to the Background Theory --- p.25 === Chapter 3.4 --- Key Factors for the Success --- p.27 === Chapter 4 --- Tasks Scheduling using Genetic Algorithms --- p.28 === Chapter 4.1 --- Details of Scheduling Problem --- p.28 === Chapter 4.2 --- Chromosome Coding --- p.32 === Chapter 4.2.1 --- Job Priority Sequence --- p.33 === Chapter 4.2.2 --- Engineer Priority Sequence --- p.33 === Chapter 4.2.3 --- An Example Chromosome Interpretation --- p.34 === Chapter 4.3 --- Fitness Evaluation --- p.37 === Chapter 4.4 --- Parent Selection --- p.38 === Chapter 4.5 --- Genetic Operators and Reproduction --- p.40 === Chapter 4.5.1 --- Job Priority Crossover (JOB-CRX) --- p.40 === Chapter 4.5.2 --- Job Priority Mutation (JOB-MUT) --- p.40 === Chapter 4.5.3 --- Engineer Priority Mutation (ENG-MUT) --- p.42 === Chapter 4.5.4 --- Reproduction: New Population --- p.42 === Chapter 4.6 --- Replacement Strategy --- p.43 === Chapter 4.7 --- The Complete Genetic Algorithm --- p.44 === Chapter 5 --- Lower Bound on Optimal Makespan --- p.46 === Chapter 5.1 --- Introduction --- p.46 === Chapter 5.2 --- Definitions and Assumptions --- p.48 === Chapter 5.2.1 --- Task Graph --- p.48 === Chapter 5.2.2 --- Graph Partitioning --- p.49 === Chapter 5.2.3 --- Activity and Load Density --- p.51 === Chapter 5.2.4 --- Assumptions --- p.52 === Chapter 5.3 --- Concepts of Lower Bound on the Minimal Time (LBMT) --- p.53 === Chapter 5.3.1 --- Previous Bound (LBMTF) --- p.53 === Chapter 5.3.2 --- Bound in other form --- p.54 === Chapter 5.3.3 --- Improved Bound (LBMTJR） --- p.56 === Chapter 5.4 --- Lower bound: Task graph reconstruction + LBMTJR --- p.59 === Chapter 5.4.1 --- Problem reduction and Assumptions --- p.60 === Chapter 5.4.2 --- Scenario I --- p.61 === Chapter 5.4.3 --- Scenario II --- p.63 === Chapter 5.4.4 --- An Example --- p.67 === Chapter 6 --- Computational Results and Discussions --- p.73 === Chapter 6.1 --- Parameterization of the GA --- p.73 === Chapter 6.2 --- Computational Results --- p.75 === Chapter 6.3 --- Performance Evaluation --- p.81 === Chapter 6.3.1 --- Solution Quality --- p.81 === Chapter 6.3.2 --- Computational Complexity --- p.86 === Chapter 6.4 --- Effects of Machines Eligibility --- p.88 === Chapter 6.5 --- Future Direction --- p.90 === Chapter 7 --- Conclusion --- p.92 === Chapter A --- Tasks data of problem sets in section 6.2 --- p.94 === Chapter A.l --- Problem 1: 19 tasks --- p.95 === Chapter A.2 --- Problem 2: 21 tasks --- p.97 === Chapter A.3 --- Problem 3: 19 tasks --- p.99 === Chapter A.4 --- Problem 4: 23 tasks --- p.101 === Chapter A.5 --- Problem 5: 27 tasks --- p.104 === Bibliography --- p.107