Waqas Haider Bangyal and Kashif Nisar and Ag. Asri Bin Ag. Ibrahim and Muhammad Reazul Haque and Joel J. P. C. Rodrigues and Danda B. Rawat (2021) Comparative Analysis of Low Discrepancy SequenceBased Initialization Approaches Using PopulationBased Algorithms for Solving the Global Optimization Problems. Applied Sciences (Switzerland), 11. pp. 136. ISSN 20763417
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Abstract
Metaheuristic algorithms have been widely used to solve diverse kinds of optimization problems. For an optimization problem, population initialization plays a significant role in metaheuristic algorithms. These algorithms can influence the convergence to find an efficient optimal solution. Mainly, for recognizing the importance of diversity, several researchers have worked on the performance for the improvement of metaheuristic algorithms. Population initialization is a vital factor in metaheuristic algorithms such as PSO and DE. Instead of applying the random distribution for the initialization of the population, quasirandom sequences are more useful for the improvement the diversity and convergence factors. This study presents three new lowdiscrepancy sequences named WELL sequence, Knuth sequence, and Torus sequence to initialize the population in the search space. This paper also gives a comprehensive survey of the various PSO and DE initialization approaches based on the family of quasirandom sequences such as Sobol sequence, Halton sequence, and uniform random distribution. The proposed methods for PSO (TOPSO, KNPSO, and WEPSO) and DE (DETO, DEWE, and DEKN) have been examined for wellknown benchmark test problems and training of the artificial neural network. The finding of our techniques shows promising performance using the family of lowdiscrepancy sequences over uniform random numbers. For a fair comparison, the approaches using lowdiscrepancy sequences for PSO and DE are compared with the other family of lowdiscrepancy sequences and uniform random number and depict the superior results. The experimental results show that the lowdiscrepancy sequencesbased initialization performed exceptionally better than a uniform random number. Moreover, the outcome of our work presents a foresight on how the proposed technique profoundly impacts convergence and diversity. It is anticipated that this lowdiscrepancy sequence comparative simulation survey would be helpful for studying the metaheuristic algorithm in detail for the researcher.
Item Type:  Article 

Keyword:  Premature convergence , Quasirandom sequences , PSO , GOP , WELL sequence , Knuth sequence; ANN 
Subjects:  Q Science > Q Science (General) > Q1390 Science (General) Q Science > QA Mathematics > QA1939 Mathematics > QA7190 Instruments and machines > QA75.576.95 Electronic computers. Computer science 
Department:  FACULTY > Faculty of Computing and Informatics 
Depositing User:  SITI AZIZAH BINTI IDRIS  
Date Deposited:  24 Mar 2022 15:23 
Last Modified:  24 Mar 2022 15:23 
URI:  https://eprints.ums.edu.my/id/eprint/32027 
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