Improved Whale Optimization Algorithm for Solving Constrained Optimization Problems DOI Creative Commons
Guiying Ning, Dunqian Cao

Discrete Dynamics in Nature and Society, Journal Year: 2021, Volume and Issue: 2021, P. 1 - 13

Published: Feb. 9, 2021

In view of the shortcomings whale optimization algorithm (WOA), such as slow convergence speed, low accuracy, and easy to fall into local optimum, an improved (IWOA) is proposed. First, standard WOA from three aspects initial population, factor, mutation operation. At same time, Gaussian introduced. Then nonfixed penalty function method used transform constrained problem unconstrained problem. Finally, 13 benchmark problems were test feasibility effectiveness proposed method. Numerical results show that IWOA has obvious advantages stronger global search ability, better stability, faster higher accuracy; it can be effectively solve complex problems.

Language: Английский

An innovative synthesis of optmization techniques (FDIRE-GSK) for generation electrical renewable energy from natural resources DOI Creative Commons
Ghada S. Mohammed, Samaher Al-Janabi

Results in Engineering, Journal Year: 2022, Volume and Issue: 16, P. 100637 - 100637

Published: Sept. 24, 2022

Based on the principle that upgrading of any nation begins by raising level performance its institutions serve community, including Ministry Electricity and given development in field technology, growing need to generate electric power, so it is found world has tended recent years energy from environmentally friendly sources do not cause CO2 emissions during generation such as solar, wind, water other sources. Finding a solution problem generating electricity very difficult important issue because one basic problems our Arab societies. The main purpose preserve environment pollution resulting process well reducing material costs production. This work deals with two points: how present optimal feasibility study for solar; generated an at lowest cost highest efficiency. paper presens find different interval renewable – Gain Shraking (FDIRE-GSK) model consists five stages: first stage collecting preparing data make suitable form decision-making included several steps, processing missing values conducting normalization work, second involved develop optimization algorithms called (Gain Knowledge optmization Algorithm (GSK). That tool select after deep analysis achieve include PSOA, BOA, WOA, EHOA, ABOA GSK; this focus determined programming parameters, advantages, disadvantages each algorithm. . GSK used intervals remove duplication, algorithm having many advantages characteristics; (a) depends limited number (b) high-accuracy performance, (c)its ability operate whose collection real-time (d) over come proplem falling local minimum; gaining sharing knowledge base also considered (e) intelligent behavior, where distinguishes others (f) finds information (Knowledge or best solutions), but only shares most information(optimal solutions). FDIRE-GSK- appear pragmatic reduce computation time handle real big data.

Language: Английский

Citations

47
A Bio-Inspired Virtual Machine Placement Toward Sustainable Cloud Resource Management DOI
Ashutosh Kumar Singh, Smruti Rekha Swain, Deepika Saxena

et al.

IEEE Systems Journal, Journal Year: 2023, Volume and Issue: 17(3), P. 3894 - 3905

Published: March 13, 2023

Virtual machine placement (VMP) is the process of selecting most appropriate physical (PM) to place users' requested virtual (VM) in large cloud data centers. Several methods have been framed deal with this problem. However, current solutions only consider limited resource types, resulting an unbalanced load that activates unnecessary PMs inside center. In article, we suggest a flower pollination-based nondominated sorting optimization (FP-NSO) algorithm maximizes usage and minimizes energy consumption carbon emission Multiple resource-constraint metrics are associated our assists finding suitable for deploying VMs environment. The VMP carried out by employing combined concept pollination technique-based genetic (NSGA-II). evaluated using Google cluster dataset. performance like utilization, power consumption, values computed static dynamic scenarios. obtained results compared existing approaches. There significant reduction emission, execution time up 16.69%, 48.60%, 75.87%, respectively, improvement utilization 78.18%.

Language: Английский

Citations

34
Bio-inspired virtual machine placement schemes in cloud computing environment: taxonomy, review, and future research directions DOI
Mohammad Masdari,

Sasan Gharehpasha,

Mostafa Ghobaei‐Arani

et al.

Cluster Computing, Journal Year: 2019, Volume and Issue: 23(4), P. 2533 - 2563

Published: Dec. 11, 2019

Language: Английский

Citations

60
An efficient power-aware VM allocation mechanism in cloud data centers: a micro genetic-based approach DOI

Mehran Tarahomi,

Mohammad Izadi, Mostafa Ghobaei‐Arani

et al.

Cluster Computing, Journal Year: 2020, Volume and Issue: 24(2), P. 919 - 934

Published: Aug. 9, 2020

Language: Английский

Citations

59
Improved Whale Optimization Algorithm for Solving Constrained Optimization Problems DOI Creative Commons
Guiying Ning, Dunqian Cao

Discrete Dynamics in Nature and Society, Journal Year: 2021, Volume and Issue: 2021, P. 1 - 13

Published: Feb. 9, 2021

In view of the shortcomings whale optimization algorithm (WOA), such as slow convergence speed, low accuracy, and easy to fall into local optimum, an improved (IWOA) is proposed. First, standard WOA from three aspects initial population, factor, mutation operation. At same time, Gaussian introduced. Then nonfixed penalty function method used transform constrained problem unconstrained problem. Finally, 13 benchmark problems were test feasibility effectiveness proposed method. Numerical results show that IWOA has obvious advantages stronger global search ability, better stability, faster higher accuracy; it can be effectively solve complex problems.

Language: Английский

Citations

53