Computational Intelligence for Optimization

1. Front Matter

   Pages i-xii

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2. Introduction

   • Nirwan Ansari, Edwin Hou

   Pages 1-10

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3. Heuristic Search Methods

   • Nirwan Ansari, Edwin Hou

   Pages 11-25

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4. Hopfield Neural Networks

   • Nirwan Ansari, Edwin Hou

   Pages 27-45

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5. Simulated Annealing and Stochastic Machines

   • Nirwan Ansari, Edwin Hou

   Pages 47-69

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6. Mean Field Annealing

   • Nirwan Ansari, Edwin Hou

   Pages 71-81

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7. Genetic Algorithms

   • Nirwan Ansari, Edwin Hou

   Pages 83-97

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8. The Traveling Salesman Problem

   • Nirwan Ansari, Edwin Hou

   Pages 99-125

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9. Telecommunications

   • Nirwan Ansari, Edwin Hou

   Pages 127-148

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10. Point Pattern Matching

    • Nirwan Ansari, Edwin Hou

    Pages 149-166

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11. Multiprocessor Scheduling

    • Nirwan Ansari, Edwin Hou

    Pages 167-188

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12. Job Shop Scheduling

    • Nirwan Ansari, Edwin Hou

    Pages 189-201

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13. Back Matter

    Pages 203-225

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The field of optimization is interdisciplinary in nature, and has been making a significant impact on many disciplines. As a result, it is an indispensable tool for many practitioners in various fields. Conventional optimization techniques have been well established and widely published in many excellent textbooks. However, there are new techniques, such as neural networks, simulated anneal­ ing, stochastic machines, mean field theory, and genetic algorithms, which have been proven to be effective in solving global optimization problems. This book is intended to provide a technical description on the state-of-the-art development in advanced optimization techniques, specifically heuristic search, neural networks, simulated annealing, stochastic machines, mean field theory, and genetic algorithms, with emphasis on mathematical theory, implementa­ tion, and practical applications. The text is suitable for a first-year graduate course in electrical and computer engineering, computer science, and opera­ tional research programs. It may also be used as a reference for practicing engineers, scientists, operational researchers, and other specialists. This book is an outgrowth of a couple of special topic courses that we have been teaching for the past five years. In addition, it includes many results from our inter­ disciplinary research on the topic. The aforementioned advanced optimization techniques have received increasing attention over the last decade, but relatively few books have been produced.

• Pattern Matching
• algorithms
• communication
• computational intelligence
• genetic algorithm
• genetic algorithms
• intelligence
• neural network
• optimization

• Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, USA

  Nirwan Ansari, Edwin Hou

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