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Hybrid Algorithms for Service, Computing and Manufacturing Systems

Book Description

In a global, highly competitive environment, organizations face increasing economic pressure and customer demands for more complex products and services. Hybrid algorithms have the potential to play an important role in helping organizations achieve cost reduction and increased product development. Hybrid Algorithms for Service, Computing and Manufacturing Systems: Routing and Scheduling Solutions explores research developments and applications from an interdisciplinary perspective that combines approaches from operations research, computer science, artificial intelligence, and applied computational mathematics. Contributions cover a range of hybrid algorithm theory and practice as it relates to routing, scheduling, and real-life applications.

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
  6. Preface
    1. PURPOSE OF THE BOOK
    2. target AUDIENCE
    3. overview of the book
  7. Acknowledgment
  8. Section 1: Hybrid Algorithms for Routing Problems
    1. Chapter 1: Matheuristics for Inventory Routing Problems
      1. Abstract
      2. Introduction
      3. 1. Problem Description
      4. 2. Evolution of Heuristics
      5. 3. Old and New Ideas for Matheuristics to Solve the Basic IRP
      6. 4. Review of Heuristics for IRPs
      7. Conclusion
    2. Chapter 2: Vehicle Routing Models and Algorithms for Winter Road Spreading Operations
      1. ABSTRACT
      2. 1. INTRODUCTION
      3. 2. OPERATIONS CONTEXT AND DECISION PROBLEMS
      4. 3. VEHICLE ROUTING MODELS FOR SPREADING
      5. 4. ANALYSIS OF EXISTING RESEARCH ON VEHICLE ROUTING PROBLEMS FOR SPREADING OPERATIONS
      6. 5. CONCLUSION AND FUTURE RESEARCH DIRECTIONS
    3. Chapter 3: Routing Solutions for the Service Industry
      1. Abstract
      2. INTRODUCTION
      3. Background
      4. MATHEMATICAL MODEL AND ALGORITHM
      5. CASE STUDIES
      6. Conclusion
    4. Chapter 4: A Hybrid Genetic Algorithm-Simulated Annealing Approach for the Multi-Objective Vehicle Routing Problem with Time Windows
      1. ABSTRACT
      2. INTRODUCTION
      3. THE MULTI-OBJECTIVE VEHICLE ROUTING PROBLEM WITH TIME WINDOWS (VRPTW): PROBLEM FORMULATION
      4. GENETIC ALGORTIHMS (GA) AND SIMULATED ANNEALING (SA): AN OVERVIEW
      5. HYBRID GENETIC ALGORITHM-SIMULATED ANNEALING APPROACH (HGASA) FOR THE MULTI-OBJECTIVE VEHICLE ROUTING PROBLEM WITH TIME WINDOWS (VRPTW)
      6. COMPUTATIONAL STUDY
      7. FUTURE RESEARCH DIRECTIONS
      8. CONCLUSION
    5. Chapter 5: Strategies for an Integrated Distribution Problem
      1. Abstract
      2. Introduction
      3. The Distribution Strategies
      4. Literature Review on VRP
      5. The Models for the Distribution Strategies
      6. Solution Approach
      7. Analysis of the Results
      8. Summary and Conclusion
    6. Chapter 6: A Hybrid Algorithm Based on Monte-Carlo Simulation for the Vehicle Routing Problem with Route Length Restrictions
      1. Abstract
      2. INTRODUCTION
      3. PREVIOUS RELATED WORK
      4. FORMAL PROBLEM DESCRIPTION AND MATHEMATICAL MODELING
      5. SOME FUNDAMENTAL IDEAS OF OUR APPROACH
      6. A HIGH-LEVEL DESCRIPTION OF OUR ALGORITHM
      7. VERIFICATION AND VALIDATION
      8. BENEFITS AND LIMITATIONS OF OUR APPROACH
      9. CONCLUSION
  9. Section 2: Hybrid Algorithms for Scheduling Problems
    1. Chapter 7: A Hybrid Particle Swarm Algorithm for Resource-Constrained Project Scheduling
      1. Abstract
      2. 1 Introduction
      3. 2 Background
      4. 3 Algorithm
      5. Solution Representation and Schedule Generation Scheme
      6. 4 Computational Results
      7. 5 Conclusion and Future Research Directions
    2. Chapter 8: Marriage in Honeybee Optimization to Scheduling Problems
      1. ABSTRACT
      2. INTRODUCTION
      3. MARRIAGE IN HONEYBEE OPTIMIZATION
      4. APPLYING MBO TO SCHEDULING PROBLEMS
      5. CONCLUSION
    3. Chapter 9: Global Bacteria Optimization Meta-Heuristic
      1. Abstract
      2. INTRODUCTION
      3. GLOBAL BACTERIA OPTIMIZATION META-HEURISTIC
      4. PERFORMANCE ANALYSIS: EXPERIMENTS ON MATHEMATICAL FUNCTIONS
      5. APPLICATION TO SOLVE SHOP SCHEDULING PROBLEMS
      6. CONCLUDING REMARKS
    4. Chapter 10: Hybrid Algorithms for Manufacturing Rescheduling
      1. ABSTRACT
      2. INTRODUCTION
      3. LITERATURE REVIEW
      4. MEASUREMENT METHODOLOGY
      5. CASE STUDIES FOR CUSTOMISED PRODUCTION
      6. RECOMMENDATIONS TO CASE STUDY COMPANIES
      7. Discussion of Results
      8. CONCLUSION
  10. Section 3: Other Applications of Hybrid Algorithms
    1. Chapter 11: HMIP Model for a Territory Design Problem with Capacity and Contiguity Constraints
      1. ABSTRACT
      2. INTRODUCTION
      3. BACKGROUND AND SOME APPLICATIONS FOR TERRITORY DESIGN
      4. PREVIOUS SOLUTION APPROACHES FOR TERRITORY DESIGN
      5. TERRITORY DESIGN APPLICATION AT EMBOTELLADORAS ARCA
      6. HMIP MODEL FOR TERRITORY DESIGN PROBLEM
      7. IMPLEMENTATION AND RESULTS
      8. ACHIEVEMENTS AND SAVINGS
      9. MODEL APPROACH CONTRIBUTION AND APPLICABILITY
      10. CONCLUSION
    2. Chapter 12: Hybrid Heuristics for the Territory Alignment Problem
      1. ABSTRACT
      2. 1 INTRODUCTION
      3. 2 BACKGROUND OF TERRITORY DESIGN
      4. 3 THE MULTIACE ALGORITHM
      5. 4 IMPLEMENTATION AND APPLICATION
      6. 5 ALGORITHM’S EFFICIENCY
      7. 6 SOLVING REAL PROBLEMS
      8. 7 FUTURE RESEARCH DIRECTIONS
      9. 8 CONCLUSION
    3. Chapter 13: A Hybrid Lagrangian Relaxation and Tabu Search Method for Interdependent-Choice Network Design Problems
      1. ABSTRACT
      2. INTRODUCTION
      3. INTEGRATION OF LAGRANGIAN RELAXATION AND TABU SEARCH
      4. A LANE-BASED NETWORK DESIGN PROBLEM WITH INTERDEPENDENT-CHOICE CONSTRAINTS
      5. IMPLEMENTATION OF THE LR-TS METHOD
      6. EXAMPLE APPLICATION AND EVALUATION
      7. CONCLUSION
  11. About the Contributors