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Logistics Management and Optimization through Hybrid Artificial Intelligence Systems

Book Description

Hybrid Artificial Intelligent Systems (HAIS) try to deal with the complexity of real world phenomena using a multidisciplinary approach and a plurality of techniques. Logistics Management and Optimization through Hybrid Artificial Intelligence Systems offers the latest research within the field of HAIS, surveying the broad topics and collecting case studies, future directions, and cutting edge analyses. Using biologically-inspired algorithms such as ant colony optimization and particle swarm optimization, this text includes solutions and heuristics for practitioners and academics alike, offering a vital resource for staying abreast in this ever-burgeoning field.

Table of Contents

  1. Cover
  2. Title Page
  3. Copyright Page
  4. Editorial Advisory Board and List of Reviewers
    1. Editorial Advisory Board
    2. List of Reviewers
  5. Foreword
    1. LOGISTICS
    2. OPTIMIZATION
    3. SOCIAL APPLICATIONS
    4. TECHNOLOGICAL
  6. Preface
  7. Acknowledgment
  8. Section 1: Logistics of Products and Services
    1. Chapter 1: Logistics Applied to Improve Bottling Water Distribution
      1. ABSTRACT
      2. INTRODUCTION
      3. JUSTIFICATION OF THE LOGISTICS RESEARCH
      4. VEHICLE ROUTING PROBLEM
      5. THE SIMULATION OF DATA TO VEHICLE ROUTING PROBLEM
      6. THE TIME-DEPENDENT POISSON PROCESS
      7. PROPOSED CULTURAL ALGORITHM
      8. PARTIALLY DYNAMIC VEHICLE ROUTING
      9. EXTENSIONS
      10. CONCLUSION AND FUTURE RESEARCH
    2. Chapter 2: Logistics for the Garbage Collection through the use of Ant Colony Algorithms
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. THE VEHICLE ROUTING PROBLEM
      4. 3. ANT COLONY OPTIMIZATION
      5. 4. ANT COLONY OPTIMIZATION ALGORITHM TO SOLVE THE WASTE COLLECTION ROUTE PROBLEM
      6. 5. CONCLUSION AND FUTURE RESEARCH
    3. Chapter 3: Grid Platform Applied to the Vehicle Routing Problem with Time Windows for the Distribution of Products
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. VRPTW MODEL
      5. GENETIC ALGORITHM IN THE GRID ENVIRONMENT FOR THE VRPTW
      6. EXPERIMENTAL MINIGRID INFRASTRUCTURE
      7. EXPERIMENTAL TESTS
      8. FUTURE WORK
      9. CONCLUSION
  9. Section 2: Improve of Optimization Applied Intelligent Techniques
    1. Chapter 4: Hybrid Algorithm Applied to the Identification of Risk Factors on the Health of Newly Born in Mexico
      1. ABSTRACT
      2. INTRODUCTION
      3. IDENTIFICATION OF RISK FACTORS DURING PREGNANCY
      4. FEATURE SUBSET SELECTION
      5. GENETIC ALGORITHM
      6. TESTORS AND TYPICAL TESTORS
      7. HYBRIDIZATION
      8. THE FRAMEWORK
      9. EXPERIMENTATION AND RESULTS
      10. CONCLUSION AND FUTURE RESEARCH
    2. Chapter 5: An Evolutionary Algorithm for Graph Drawing with a Multiobjective Approach
      1. ABSTRACT
      2. INTRODUCTION
      3. OPTIMIZATION PROBLEM, SOLUTION REPRESENTATION AND EVALUATION FUNCTIONS
      4. DESCRIPTION OF THE ALGORITHMIC COMPONENTS OF MOEA-HCEDA ALGORITHM
      5. MULTIOBJECTIVE OPTIMIZATION
      6. PROPOSED HYBRID MOEA-HCEDA ALGORITHM
      7. EXPERIMENT DESIGN, RESULTS AND DISCUSSION
      8. GENERAL CONCLUSION
      9. FUTURE RESEARCH
    3. Chapter 6: Handwritten Signature Verification Using Multi-Objective Optimization with Genetic Algorithms in a Forensic Architecture
      1. ABSTRACT
      2. OBJECTIVE AND OUTLINE OF THIS CHAPTER
      3. INTRODUCTION
      4. AUTOMATIC VERIFICATION OF HANDWRITTEN SIGNATURES
      5. VARIABLES, FEATURES AND PROTOTYPE FUNCTIONS IN SIGNATURES
      6. MULTI-OBJECTIVE OPTIMIZATION FOR AUTOMATIC VERIFICATION OF SIGNATURES
      7. FORENSIC ARCHITECTURE OF SIGNATURE VERIFICATION
      8. ELEMENTS OF COMPARISON
      9. CLASSIFICATION BASED ON NND-FR SYSTEMS
      10. EXPERIMENTAL EVALUATION AND RESULTS
      11. RESULTS AND DISCUSSION
      12. CONCLUSION AND FUTURE WORK
    4. Chapter 7: Looking for Reverse Transformations between NP-Complete Problems
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. BACKGROUND
      4. 3. ANOMALY IN THE TRANSFORMATION BETWEEN THE PARTITION AND THE BIN PACKING PROBLEMS
      5. 4. CHECKING THE NP-COMPLETENESS OF THE PARTITION PROBLEM
      6. 5. THREE-HOP REVERSE TRANSFORMATION FROM PARTITION TO SAT
      7. 6. FUTURE RESEARCH DIRECTIONS
      8. 7. CONCLUSION
    5. Chapter 8: Variants of VRP to Optimize Logistics Management Problems
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND
      4. ORIGIN OF VRP
      5. THE VEHICLE ROUTING PROBLEM
      6. VARIANTS OF VRP
      7. VEHICLE ROUTING PROBLEM WITH TIME WINDOWS
      8. RICH VRP
      9. BIN PACKING PROBLEM
      10. THE ROUTING, SCHEDULING AND LOADING PROBLEM
      11. HEURISTIC METHODS
      12. ANT COLONY SYSTEM
      13. RANDOM PROPORTIONAL RULE
      14. STATE TRANSITION RULE
      15. GLOBAL UPDATE RULE
      16. LOCAL UPDATE RULE
      17. ELECTION OF THE ALGORITHM FOR ALLOCATION OF ROUTES AND SCHEDULES
      18. EXPERIMENT CONDITION
      19. COMPLEXITY
      20. COMPLEXITY OF ROUTE ALLOCATION
      21. COMPLEXITY ALLOCATION SCHEDULE
      22. COMPLEXITY IN THE ALLOCATION OF LOADS
      23. COMPLEXITY
      24. SOLUTION METHODOLOGY
      25. SOLUTION ALGORITHM
      26. COMPUTATION OF THE HEURISTIC INFORMATION
      27. SELF-ADAPTIVE CONSTRAINED LIST
      28. INITIAL SEARCH
      29. LOCAL SEARCH
      30. ANT COLONY SYSTEM FOR ALLOCATION OF ROUTES, SCHEDULES AND LOADS
      31. EXPERIMENTATION AND RESULT
      32. TEST INSTANCES
      33. THEORETICAL EXPERIMENTATION
      34. EXPERIMENTING WITH REAL CASES
      35. FUTURE RESEARCH DIRECTIONS
      36. CONCLUSION
    6. Chapter 9: Heuristic Algorithms
      1. ABSTRACT
      2. INTRODUCTION
      3. RoSLoP: ROUTING, SCHEDULING AND LOADING PROBLEM
      4. BIN PACKING PROBLEM (BPP)
      5. METHODOLOGY OF RoSLoP SOLUTION
      6. DiPro ALGORITHM
      7. GENETIC ALGORITHM FOR BPP: HGGA-BP-I
      8. EXPERIMENTATION WITH THE TRANSPORTATION SYSTEMS
      9. CONCLUSION AND FUTURE WORK
    7. Chapter 10: Recombination Operators in Permutation-Based Evolutionary Algorithms for the Travelling Salesman Problem
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. THE TRAVELLING SALESMAN PROBLEM
      4. 3. GENETIC ALGORITHMS FOR TSP
      5. 4. CROSSOVER OPERATORS FOR PERMUTATION BASED ENCODING
      6. 5. PROPOSED RECOMBINATION OPERATORS
      7. 6. EXPERIMENTAL RESULTS
      8. 7. CONCLUSION
  10. Section 3: Social Application on Logistic
    1. Chapter 11: Crowdfunding to improve Environmental Projects’ Logistics
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. CROWDFUNDING AS A DIFFERENT WAY TO OBTAIN FUNDS TO AN ENVIRONMENTAL PROJECTS
      4. 3. APPLIED CROWDFUNDING TO AN ENVIRONMENTAL REAL PROJECT
      5. 4. CURRENT STUDY
      6. 5. EXPERIMENTS
      7. 6. CONCLUSION
      8. 7. DISCUSSIONS AND FUTURE RESEARCH
    2. Chapter 12: Improve Card Collection from Memory Alpha using Sociolinguistics and Japanese Puzzles
      1. ABSTRACT
      2. INTRODUCTION
      3. SUPPLEMENTAL ANALYSIS: THE CASE OF THE “BIG-MARKET” TEAM
    3. Chapter 13: Mass Media Strategies
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. UNDERSTANDING HYBRID APPROACHES
      4. 3. MARKET ANALYSIS BY MASS MEDIA
      5. 4. CASES OF STUDY
      6. 5. CROWFUNDING AS A DIFFERENT WAY TO OBTAIN FUNDS TO A PROJECT
      7. 6. APPLIED CROWDFUNDING A REAL PROJECT
      8. 7. EXPERIMENTS TO SUPPORT AN INDIE POP BAND
      9. 8. EXPERIMENTS RELATED WITH A WRESTLING CIRCUIT
      10. 9. CONCLUSION AND FUTURE RESEARCH
  11. Section 4: Technological Application using Intelligent Optimization
    1. Chapter 14: Optimization of a Hybrid Methodology (CRISP-DM)
      1. ABSTRACT
      2. 1. BRIEF HISTORY
      3. 2. CRISP-DM METHODOLOGY
      4. 3. THE CRISP-DM REFERENCE MODEL
      5. 4. DATA ACCESS STANDARDS
      6. 5. MODEL GENERATION STANDARDS
      7. 6. MODEL REPRESENTATION STANDARDS
      8. 7. CONCLUSION
    2. Chapter 15: Data Mining Applications in the Electrical Industry
      1. ABSTRACT
      2. INTRODUCTION
      3. PARTIAL DISCHARGE: CONCEPTS
      4. DIAGNOSIS ON POWER CABLES: OVERVIEW USING DATA MINING TOOLS
      5. SELF ORGANIZING MAPS (SOM) AND HIERARCHICAL CLUSTERING
      6. ANALYSIS OF PD DATA
      7. CONCLUSION AND FUTURE WORKS
    3. Chapter 16: Decision Making Approaches for Advanced Manufacturing Technology Evaluation and Selection
      1. ABSTRACT
      2. INTRODUCTION
      3. ADVANCED MANUFACTURING TECHNOLOGY (AMT)
      4. AMT BENEFITS
      5. MULTI-ATTRIBUTE TECHNIQUES (MAT)
      6. TOPSIS
      7. INTEGRATIVE EXAMPLE
      8. ERGONOMICS AND SAFETY ATTRIBUTES IN THE SELECTION OF AMT: AN ERGONOMIC APPROACH FOR THEIR EVALUATION
      9. CONCLUSION
    4. Chapter 17: Optical Application improved with Logistics of Artificial Intelligent and Electronic Systems
      1. ABSTRACT
      2. OTHER APPLICATIONS OF ELECTRONICS SYSTEMS: IRRADIANCE METERS
      3. IRRADIANCE METERS FOR CONVERGENT SOURCES: OTHER APPLICATION OF THE XY TABLE AUTOMATION
      4. EXPERIMENTAL RESULTS
      5. CONCLUSION
    5. Chapter 18: Optimization of the Impeller and Diffuser of Hydraulic Submersible Pump using Computational Fluid Dynamics and Artificial Neural Networks
      1. ABSTRACT
      2. INTRODUCTION
      3. DESIGN
      4. COMPUTATIONAL FLUID DYNAMICS
      5. ARTIFICIAL NEURAL NETWORKS
      6. METHODOLOGY
      7. CONCLUSION
  12. Compilation of References
  13. About the Contributors