You are previewing Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics.
O'Reilly logo
Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics

Book Description

Modern optimization approaches have attracted many research scientists, decision makers and practicing researchers in recent years as powerful intelligent computational techniques for solving several complex real-world problems. The Handbook of Research on Modern Optimization Algorithms and Applications in Engineering and Economics highlights the latest research innovations and applications of algorithms designed for optimization applications within the fields of engineering, IT, and economics. Focusing on a variety of methods and systems as well as practical examples, this book is a significant resource for graduate-level students, decision makers, and researchers in both public and private sectors who are seeking research-based methods for modeling uncertain real-world problems. .

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Book Series
    1. Mission
    2. Coverage
  5. Editorial Advisory Board and List of Reviewers
    1. Editorial Advisory Board
    2. List of Reviewers
  6. Foreword
  7. Foreword
  8. Foreword
  9. Preface
  10. Acknowledgment
  11. Chapter 1: Optimization Algorithms in Local and Global Positioning
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. POSITION ESTIMATION IN GLOBAL POSITIONING SYSTEM
    5. LOCAL POSITIONING SYSTEMS
    6. COMBINING VARIOUS MEASUREMENTS AND TECHNOLOGIES
    7. FUTURE RESEARCH DIRECTIONS
    8. CONCLUSION
    9. REFERENCES
    10. ADDITIONAL READING
    11. KEY TERMS AND DEFINITIONS
  12. Chapter 2: Robust Two-Stage and Multistage Optimization
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BACKGROUND: ROBUST 2-STAGE (LINEAR) OPTIMIZATION PROBLEMS
    4. 3. ROBUST MULTISTAGE OPTIMIZATION PROBLEMS
    5. 4. STATE-SPACE REPRESENTABLE ROBUST MULTISTAGE PROBLEMS AND THEIR EFFICIENT SOLUTION
    6. 5. APPLICATION TO A MULTIPERIOD ENERGY PRODUCTION PROBLEM UNDER UNCERTAINTY
    7. 6. CONCLUSION
    8. 7. FUTURE RESEARCH DIRECTIONS
    9. ACKNOWLEDGMENT
    10. REFERENCES
    11. ADDITIONAL READING
    12. KEY TERMS AND DEFINITIONS
    13. APPENDIX. SOME USEFUL PROBABILISTIC RESULTS ON DISCRETE MARKOV CHAINS
  13. Chapter 3: Supply Chain Network Design Using an Enhanced Hybrid Swarm-Based Optimization Algorithm
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. THE BEES ALGORITHM AND SLOPE ANGLE COMPUTATION AND HILL CLIMBING ALGORITHM
    5. SUPPLY NETWORK DESIGN CASE STUDY AND METHODOLOGY
    6. RESULTS
    7. FUTURE RESEARCH DIRECTIONS
    8. CONCLUSION
    9. REFERENCES
    10. KEY TERMS AND DEFINITIONS
  14. Chapter 4: Real World Applications
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. WHAT IS SUPPLY CHAIN MANAGEMENT?
    5. TOTAL ASSET VISIBILITY
    6. TRANSPORTATION IMPACTING SUPPLY CHAIN MANAGEMENT AND TOTAL ASSET VISIBILITY
    7. OPTIMIZATION IMPACTING SUPPLY CHAIN MANAGEMENT AND TOTAL ASSET VISIBILITY
    8. PACKAGING, SUPPLY CHAIN MANAGEMENT, AND TOTAL ASSET VISIBILITY
    9. LIMITATION OF THIS RESEARCH WORK
    10. FUTURE RESEARCH DIRECTIONS
    11. CONCLUSION
    12. CASE STUDIES
    13. DISCUSSION TOPICS
    14. REFERENCES
    15. ADDITIONAL READING
    16. KEY TERMS AND DEFINITIONS
    17. NOMENCLATURE/ABBREVIATION FOR ACRONYMS
  15. Chapter 5: Variable Selection in Multiple Linear Regression Using a Genetic Algorithm
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. METHODOLOGY
    5. DISCUSSION
    6. FUTURE RESEARCH DIRECTIONS
    7. CONCLUSION
    8. ACKNOWLEDGMENT
    9. REFERENCES
    10. ADDITIONAL READING
    11. KEY TERMS AND DEFINITIONS
    12. APPENDIX: NOMENCLATURE
  16. Chapter 6: An Application of Alpha-Stable Distributions for the Economic Analysis of Unit Commitment
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. STABLE DISTRIBUTIONS
    4. 3. THE MULTIPERIOD UNIT COMMITMENT MODEL
    5. 4. SOLVING STRATEGIES
    6. 5. TEST SYSTEMS GENERATION
    7. 6. COMPUTATIONAL RESULTS
    8. 7. FUTURE RESEARCH DIRECTIONS
    9. 8. CONCLUSION
    10. ACKNOWLEDGMENT
    11. REFERENCES
    12. ADDITIONAL READING
    13. KEY TERMS AND DEFINITIONS
  17. Chapter 7: Stochastic Optimization of Manufacture Systems by Using Markov Decision Processes
    1. ABSTRACT
    2. 1 INTRODUCTION
    3. 2 BACKGROUND MODEL
    4. 3 PROBLEM DEFINITIONS
    5. 4 NUMERICAL EXAMPLE
    6. CONCLUSION
    7. ACKNOWLEDGMENT
    8. REFERENCES
    9. APPENDIX 1: NUMERICAL RESULTS
  18. Chapter 8: A Genetic Algorithm's Approach to the Optimization of Capacitated Vehicle Routing Problems
    1. ABSTRACT
    2. INTRODUCTION
    3. ADDITIONAL READINGS
    4. DEFINITION OF THE CVRP
    5. METHODOLOGY
    6. EXPERIMENTS AND COMPARISONS
    7. A REAL-WORLD APPLICATION
    8. FUTURE RESEARCH DIRECTIONS
    9. CONCLUSION
    10. ACKNOWLEDGMENT
    11. REFERENCES
    12. KEY TERMS AND DEFINITIONS
    13. ACRONYMS USED IN THE TEXT
    14. APPENDIX 1: FIGURES
    15. APPENDIX 2: INPUT DATA FROM THE REAL-WORLD PROBLEM
  19. Chapter 9: Application of Artificial Bee Colony Algorithms to Antenna Design Problems for RFID Applications
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. RESULTS AND DISCUSSIONS
    5. DISCUSSION
    6. FUTURE RESEARCH DIRECTIONS
    7. LIMITATION
    8. CONCLUSION
    9. ACKNOWLEDGMENT
    10. REFERENCES
    11. ADDITIONAL READING
    12. KEY TERMS AND DEFINITIONS
    13. ACRONYMS USED IN THE TEXT
    14. APPENDIX: INPUT DATA FOR THE RFID DESING CASES
  20. Chapter 10: Optimization of Traffic Network Design Using Nature-Inspired Algorithm
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. ORIGIN-DESTINY TRAFFIC ASSIGNMENT PROBLEM (ODTAP)
    5. LIMITATIONS
    6. CONCLUSION
    7. FUTURE RESEARCH DIRECTIONS
    8. ACKNOWLEDGMENT
    9. REFERENCES
    10. ADDITIONAL READING
    11. KEY TERMS AND DEFINITIONS
    12. ENDNOTES
  21. Chapter 11: Hybrid Cuckoo Search Algorithm for Optimal Placement and Sizing of Static VAR Compensator
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. PROPOSED HYBRID CUCKOO SEARCH ALGORITHM
    5. OPTIMAL PLACEMENT AND SIZING OF SVC DEVICES
    6. THE FITNESS FUNCTION AND IMPLEMENTATION
    7. NUMERICAL RESULTS
    8. FUTURE RESEARCH DIRECTIONS
    9. CONCLUSION
    10. REFERENCES
    11. ADDITIONAL READING
    12. KEY TERMS AND DEFINITIONS
    13. ABBREVIATION
    14. NOMENCLATURE
    15. APPENDIX
  22. Chapter 12: Modeling a Real Cable Production System as a Single Machine-Scheduling Problem
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. CASE STUDY
    4. 3. EXACT MATHEMATICAL FORMULATION
    5. 4. SOLUTION METHODOLOGY
    6. 5. COMPUTATIONAL EXPERIMENTS
    7. 6. CONCLUSION
    8. ACKNOWLEDGMENT
    9. REFERENCES
  23. Chapter 13: Hybrid Genetics Algorithms for Multiple Sequence Alignment
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. THE CONSISTENT CASE
    5. THE INCONSISTENT CASE
    6. SIMULATION
    7. DISCUSSION
    8. FUTURE RESEARCH DIRECTIONS
    9. CONCLUSION
    10. ACKNOWLEDGMENT
    11. REFERENCES
    12. ADDITIONAL READING
    13. KEY TERMS AND DEFINITIONS
  24. Chapter 14: Cuckoo Search Algorithm for Hydrothermal Scheduling Problem
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. LIMITATION OF THE RESEARCH
    5. CUCKOO SEARCH ALGORITHM
    6. MODIFIED CUCKOO SEARCH ALGORITHM
    7. HYDROTHERMAL SCHEDULING PROBLEM
    8. IMPLEMENTATION OF CSA FOR HYDROTHERMAL SCHEDULING PROBLEM
    9. IMPLEMENTATION OF MCSA FOR HYDROTHERMAL SCHEDULING PROBLEM
    10. NUMERICAL RESULTS
    11. FUTURE RESEARCH DIRECTIONS
    12. CONCLUSION
    13. REFERENCES
    14. ADDITIONAL READING
    15. KEY TERMS AND DEFINITIONS
    16. NOMENCLATURE
  25. Chapter 15: Imprecise Solutions of Ordinary Differential Equations for Boundary Value Problems Using Metaheuristic Algorithms
    1. ABSTRACT
    2. INTRODUCTION
    3. PROPOSED ESTIMATED METHOD
    4. METAHEURISTIC OPTIMIZATION ALGORITHMS
    5. TESTED ODES
    6. NUMERICAL OPTIMIZATION RESULTS AND DISCUSSIONS
    7. CONCLUSION
    8. ACKNOWLEDGMENT
    9. REFERENCES
    10. KEY TERMS AND DEFINITIONS
  26. Chapter 16: A Service Cost-Base Supply Balance of Sustainable Power Generation
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. EVALUATION OF RELIABILITY
    4. 3. BUILDING A RELIABILITY EVALUATION MODEL FOR POWER GENERATION SYSTEMS WITH SOLAR AND WIND ENERGY
    5. 4. CONCLUSION
    6. REFERENCES
  27. Chapter 17: Software Module Clustering Using Bio-Inspired Algorithms
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. RESEARCH OBJECTIVES
    5. MAIN FOCUS OF THE CHAPTER
    6. EXPERIMENTAL SETUP
    7. RESULT AND ANALYSIS
    8. THREAT TO VALIDITY
    9. CONCLUSION
    10. FUTURE WORK
    11. ACKNOWLEDGMENT
    12. REFERENCES
    13. KEY TERMS AND DEFINITIONS
  28. Chapter 18: Hybrid Particle Swarm and Gravitational Search Optimization Techniques for Charging Plug-In Hybrid Electric Vehicles
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. MAIN FOCUS OF THE CHAPTER
    5. PROPOSED METHODS
    6. FUTURE RESEARCH DIRECTIONS
    7. CONCLUSION
    8. ACKNOWLEDGMENT
    9. REFERENCES
    10. ADDITIONAL READING
    11. KEY TERMS AND DEFINITIONS
    12. APPENDIX: NOMENCLATURE
  29. Chapter 19: Planning of a Project with Imprecise Activity Time
    1. ABSTRACT
    2. INTRODUCTION
    3. ARITHMETIC AND RANKING OF IMPRECISE NUMBERS
    4. THE ALGORITHMS
    5. CONCLUSION
    6. REFERENCES
  30. Chapter 20: Swarm Intelligence for Multiobjective Optimization of Extraction Process
    1. ABSTRACT
    2. INTRODUCTION
    3. INDUSTRIAL MULTIOBJECTIVE OPTIMIZATION
    4. PARETO FRONTIER AND DOMINANCE LEVELS
    5. PROBLEM DESCRIPTION
    6. NORMAL BOUNDARY INTERSECTION METHOD
    7. SWARM INTELLIGENCE
    8. MEASUREMENT INDICATORS
    9. COMPUTATIONAL RESULTS AND ANALYSIS
    10. CONCLUSION
    11. FUTURE RESEARCH DIRECTIONS
    12. ACKNOWLEDGMENT
    13. REFERENCES
    14. ADDITIONAL READING
    15. KEY TERMS AND DEFINITIONS
    16. APPENDIX: MISCELLANEOUS DATA
  31. Chapter 21: Verification of Iterative Methods for the Linear Complementarity Problem
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. PREREQUISITE
    5. PROJECTIVE ITERATIVE METHODS
    6. KRYLOV SUBSPACE METHODS FOR LCP(A, q)
    7. PRECONDITIONED GAUSS-SEIDEL(PGS)ITERATIVE METHOD FOR LCP (A, q)
    8. NUMERICAL RESULTS
    9. CONCLUSION
    10. REFERENCES
  32. Chapter 22: Parameter Optimization of Photovoltaic Solar Cell and Panel Using Genetic Algorithms Strategy
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. OPTIMIZATION PARAMETERS SOLAR CELL: THEORY AND FORMULATION
    5. SOLAR CELL PARAMETERS EXTRACTION
    6. RESULTS AND DISCUSSION
    7. CONCLUSION
    8. FUTURE RESEARCH DIRECTIONS
    9. REFERENCES
    10. ADDITIONAL REFERENCES
    11. KEY TERMS AND DEFINITIONS
  33. Chapter 23: Dantzig-Wolfe Decomposition and Lagrangean Relaxation-Based Heuristics for an Integrated Production and Maintenance Planning with Time Windows
    1. ABSTRACT
    2. I. INTRODUCTION
    3. II. PROBLEM DESCRIPTION AND MATHEMATICAL FORMULATION
    4. III. HEURISTIC FOR ULSP-TW-SC
    5. IV. HEURISTICS FOR INTEGRATED PROBLEM
    6. V. COMPUTATIONAL RESULTS
    7. VI. CONCLUSION AND PERSPECTIVE
    8. REFERENCES
  34. Chapter 24: TOPSIS in Generalized Intuitionistic Fuzzy Environment
    1. ABSTRACT
    2. INTRODUCTION
    3. BACKGROUND
    4. PRELIMINARIES
    5. AN INTEGRATED GENERALIZED INTUITIONISTIC FUZZY MULTI-CRITERIA DECISION MAKING METHOD
    6. ILLUSTRATE EXAMPLE
    7. CONCLUSION
    8. REFERENCES
  35. Chapter 25: Bi-Criteria Optimization for Finding the Optimal Replacement Interval for Maintaining the Performance of the Process Industries
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. RELATED WORKS AND BACKGROUND
    4. 3. NOTATIONS AND ASSUMPTION
    5. 4. MAINTENANCE PLANNING AND SCHEDULING
    6. 5. BIOGEOGRAPHY BASED OPTIMIZATION
    7. 6. AN ILLUSTRATIVE EXAMPLE
    8. 7. CONCLUSION
    9. 8. FUTURE RESEARCH DIRECTIONS
    10. REFERENCES
    11. ADDITIONAL READING
    12. KEYTERMS AND DEFINITIONS
  36. Chapter 26: Performances of Adaptive Cuckoo Search Algorithm in Engineering Optimization
    1. ABSTRACT
    2. INTRODUCTION
    3. RELATED WORKS
    4. BACKGROUND
    5. THE PROPOSED ADAPTIVE CUCKOO SEARCH ALGORITHM
    6. OPTIMIZATION OF BENCHMARK FUNCTION
    7. REAL WORLD APPLICATION
    8. REAL WORLD ENGINEERING APPLICATION: OPTIMIZATION OF PULP AND PAPER PROPERTIES
    9. FUTURE RESEARCH DIRECTIONS
    10. CONCLUSION
    11. REFERENCES
    12. ADDITIONAL READING
    13. KEY TERMS AND DEFINITIONS
  37. Chapter 27: Gravitational Search Algorithm
    1. ABSTRACT
    2. 1 INTRODUCTION
    3. 2 GRAVITATIONAL SEARCH ALGORITHM
    4. 3 OPERATORS IN GRAVITATIONAL SEARCH ALGORITHM
    5. 4 OVERVIEW OF GSA’S VARIANTS
    6. 5 HYBRID GRAVITATIONAL SEARCH ALGORITHM
    7. 6 PARAMETER ADAPTATION AND CONTROL SCHEMES FOR GSA
    8. 7 CONCLUSION AND FUTURE RESEARCH DIRECTION
    9. ACKNOWLEDGMENT
    10. REFERENCES
    11. KEY TERMS AND DEFINITIONS
  38. Chapter 28: Single Batch-Processing Machine Scheduling Problem with Fuzzy Due-Dates
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. FUZZY MATHEMATICAL MODEL AND PROBLEM DESCRIPTIONS
    4. 3. SOLUTION APPROACH
    5. 4. COMPUTATIONAL EXPERIMENTS
    6. 5. CONCLUSION AND FUTURE RESEARCH DIRECTIONS
    7. REFERENCES
  39. Chapter 29: Innovative Hierarchical Fuzzy Logic for Modelling Using Evolutionary Algorithms
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. VARIABLE SELECTION AND RULE BASE DECOMPOSITION
    4. 3. RULE BASE IDENTIFICATION
    5. 4 CO-EVOLUTIONARY LEARNING
    6. 5. CONCLUSION
    7. ACKNOWLEDGMENT
    8. REFERENCES
  40. Chapter 30: Solving Non-Linear Bi-Level Programming Problem Using Taylor Algorithm
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. THE NON-LINEAR BLPP AND SMOOTHING METHOD
    4. 3. MAIN THEORETICAL RESULTS
    5. 4. COMPUTATIONAL RESULTS
    6. 5. CONCLUSION AND FUTURE WORK
    7. REFERENCES
  41. Chapter 31: Some Aspects of Energy Efficiency for Refrigeration and Air Conditioning
    1. ABSTRACT
    2. INTRODUCTION
    3. EARTH-ENERGY SYSTEMS (EESs)
    4. AIR DISTRIBUTION
    5. DISCUSSIONS
    6. CONCLUSION
    7. REFERENCES
  42. Chapter 32: Modeling and Monitoring of Chemical System
    1. ABSTRACT
    2. INTRODUCTION
    3. RELATED WORKS
    4. PROBLEM STATEMENT
    5. DESCRIPTION OF VARIATIONAL BAYESIAN FILTERING TECHNIQUE
    6. STATE AND PARAMETER ESTIMATION OF A CSTR PROCESS
    7. FUTURE RESEARCH DIRECTIONS
    8. CONCLUSION
    9. ACKNOWLEDGMENT
    10. REFERENCES
    11. ADDITIONAL READING
    12. KEY TERMS AND DEFINITIONS
  43. Compilation of References
  44. About the Contributors