You are previewing International Journal of Applied Evolutionary Computation (IJAEC) Volume 7, Issue 2.
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International Journal of Applied Evolutionary Computation (IJAEC) Volume 7, Issue 2

Book Description

The International Journal of Applied Evolutionary Computation (IJAEC) covers state-of-the-art interdisciplinary research on emerging areas and of intelligent computation (IC). By providing an academic and scientific forum for exchanging high quality results on innovative topics, trends and research in the field of IC, this journal expands the fields and the depths of its most principal and critical concepts. IJAEC extends existing research findings (theoretical innovations and modeling applications) to provide the highest quality original concepts, hybrid applications, innovative methodologies, and the development trends studies for all audiences. IJAEC publishes three categories of papers: research papers, research notes, and research review. Research papers have significant original research findings. The research must be complete and contribute substantially to knowledge in the field. Research notes comprise research that is complete but not as comprehensive as to meet the criteria of a full research paper. Research reviews are novel, insightful, and carefully crafted articles that conceptualize research areas and synthesize prior research. Research review articles must provide new insights that advance our understanding of the research areas and help in identifying and developing future research directions.

This issue contains the following articles:

  • A Hybrid Algorithm Using Genetic Algorithm and Cuckoo Search Algorithm to Solve Job Scheduling Problem in Computational Grid Systems
  • Efficient Mutation Strategies Embedded in Laplacian-Biogeography-Based Optimization Algorithm for Unconstrained Function Minimization
  • Density and Distance Based KNN Approach to Classification
  • A New Approach of Dynamic Load Balancing Scheduling Algorithm for Homogeneous Multiprocessor System
  • Meta-Heuristic Algorithms to Solve Bi-Criteria Parallel Machines Scheduling Problem

Table of Contents

  1. Cover
  2. Masthead
  3. Call For Articles
  4. A Hybrid Algorithm Using Genetic Algorithm and Cuckoo Search Algorithm to Solve Job Scheduling Problem in Computational Grid Systems
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. RELATED WORKS
    4. 3. PROBLEM DEFINITION
    5. 4. GENETIC ALGORITHM
    6. 5. CUCKOO SEARCH ALGORITHM
    7. 6. ANT COLONY OPTIMIZATION
    8. 7. PROPOSED HYBRID ALGORITHM
    9. 8. EXPERIMENTS AND RESULTS
    10. 9. CONCLUSION
    11. REFERENCES
  5. Efficient Mutation Strategies Embedded in Laplacian-Biogeography-Based Optimization Algorithm for Unconstrained Function Minimization
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BIOGEOGRAPHY-BASED OPTIMIZATION
    4. 3. LAPLACIAN BBO
    5. 4. PROPOSED VERSIONS OF LX-BBO
    6. 5. NUMERICAL EXPERIMENTS
    7. 6. STATISTICAL ANALYSIS
    8. 7. SOLVING CAMERA CALIBRATION PROBLEM
    9. 8. CONCLUSION AND FUTURE SCOPE
    10. REFERENCES
  6. Density and Distance Based KNN Approach to Classification
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. BACKGROUND
    4. 3. DESIGN
    5. 4. EXPERIMENTAL RESULTS AND EVALUATIONS
    6. 5. FURTHER STUDY
    7. 6. CONCLUSION
    8. ACKNOWLEDGMENT
    9. REFERENCES
  7. A New Approach of Dynamic Load Balancing Scheduling Algorithm for Homogeneous Multiprocessor System
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. PROBLEM DESCRIPTION
    4. 3. LOAD BALANCING
    5. 4. PREVIOUS WORK
    6. 5. RELATED WORK
    7. 6. PROPOSED MODEL
    8. 7. SIMULATION RESULTS AND ANALYSIS
    9. 8. CONCLUSION AND FUTURE SCOPE
    10. REFERENCES
  8. Meta-Heuristic Algorithms to Solve Bi-Criteria Parallel Machines Scheduling Problem
    1. ABSTRACT
    2. 1. INTRODUCTION
    3. 2. LITERATURE REVIEW
    4. 3. PROBLEM FORMULATION
    5. 4. PROPOSED ALGORITHMS
    6. 5. EXPERIMENTAL SETUP
    7. 6. EXPERIMENTAL RESULTS
    8. 7. CONCLUSION
    9. REFERENCES
  9. Call For Articles