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Development of Self-consistent Multi-objective Harmony Search Algorithm

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Swarm, Evolutionary, and Memetic Computing (SEMCCO 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8947))

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Abstract

This work presents the development of multi-objective harmony search (MOHS) algorithm for optimization problem using self-adaptive improved harmony search (SIHS) algorithm which is a variant of recently developed harmony search algorithm (HS) for single objective optimization. The approach used in this work is decomposing of multiple objectives into several single objective functions which are simultaneously optimized in such a way that a nearly uniform distribution of the solutions along the pareto-front is followed. The algorithm upon testing for standard test functions has shown promising results.

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Abbreviations

BW:

Band Width

DE:

Differential Evolution

DV:

Decision Variables

EA:

Evolutionary Algorithm

GA:

Genetic Algorithm

HMCR:

Harmony Memory Consideration Rate

HSA:

Harmony Search Algorithm

HS:

Harmony search

PAR:

Pitch Adjustment Rate

PF:

Pareto Front

IHS:

Improved Harmony Search

SIHS:

Self-adaptive Improved harmony search algorithm

SPEA:

Strength Pareto Evolutionary Algorithm

IHSA:

Improved Harmony Search Algorithm

MOEA:

Multi-Objective Evolutionary algorithm

MOGA:

Multi-Objective Genetic Algorithm

MOHS:

Multi-Objective Harmony Search

MOOP:

Multi-Objective Optimization Problem

NOI:

Number of Iterations

NPGA:

Niche Pareto Genetic Algorithm

NSGA:

Non-dominated Sorting Genetic Algorithm

References

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Author information

Authors and Affiliations

  1. Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati, 781039, Assam, India

    Siddharth Jain, Jaydev Kalivarapu & Swarup Bag

Authors
  1. Siddharth Jain
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  2. Jaydev Kalivarapu
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  3. Swarup Bag
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Corresponding author

Correspondence to Siddharth Jain .

Editor information

Editors and Affiliations

  1. Department of Electrical Engineering, IIT, New Delhi, India

    Bijaya Ketan Panigrahi

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore

    Ponnuthurai Nagaratnam Suganthan

  3. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, India

    Swagatam Das

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Jain, S., Kalivarapu, J., Bag, S. (2015). Development of Self-consistent Multi-objective Harmony Search Algorithm. In: Panigrahi, B., Suganthan, P., Das, S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2014. Lecture Notes in Computer Science(), vol 8947. Springer, Cham. https://doi.org/10.1007/978-3-319-20294-5_48

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  • DOI: https://doi.org/10.1007/978-3-319-20294-5_48

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-20293-8

  • Online ISBN: 978-3-319-20294-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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