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Applications of Multiobjective Particle Swarm Optimization Algorithms in Smart Grid: a Comprehensive Survey
2016
TELKOMNIKA (Telecommunication Computing Electronics and Control)
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Multiobjective particle swarm optimization (MOPSO) has powerful potential for obtaining Pareto optimal solutions of these MOPs in a run because it has advantages of parallel computation, faster convergence ...
This paper can serve a very useful purpose by providing a good reference source of MOPSO design to those interested in Multi-objective optimization issues in smart grid. ...
more efficiently. ...
doi:10.12928/telkomnika.v14i3a.4397
fatcat:kvu4ybelgrfc7au26mt6jzhwji
A comprehensive survey: Applications of multi-objective particle swarm optimization (MOPSO) algorithm
2013
Transactions on Combinatorics
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Multi-Objective PSO (MOPSO) established in 1999, has become an emerging field for solving MOOs with a large number of extensive literature, software, variants, codes and applications. ...
Particle Swarm Optimization (PSO) has been established in 1995 and became a very mature and most popular domain in SI. ...
infrastructure facilities for carrying out this work. ...
doaj:d067a695f2874248a87829b843ff1df7
fatcat:l2vav6okc5bcdaci3h2hwoktyy
Performance Evaluation and Optimization of a Photovoltaic/Thermal (PV/T) System according to Climatic Conditions
2022
Energies
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On this basis, the energy and exergy efficiencies are analyzed for a proposed PV/T system. ...
It is also found that the efficiency rates for both energy and exergy soar with a rise in the ambient temperature. ...
Methodology
Multiobjective Particle Swarm Optimization (MOPSO) There are a wide variety of methods for optimization purposes. ...
doi:10.3390/en15207489
fatcat:wbisvdapjbgivpdbmx2zvzmzpq
A Multiobjective Particle Swarm Optimization Algorithm Based on Multipopulation Coevolution for Weapon-Target Assignment
2019
Mathematical Problems in Engineering
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To solve WTA problems with multiple optimization objectives, a multipopulation coevolution-based multiobjective particle swarm optimization (MOPSO) algorithm is proposed to realize the rapid search for ...
The simulation results show that the proposed algorithm has higher computational efficiency and achieves better solutions than existing algorithms capable of providing a good solution. ...
The simulation results show that the method is more efficient than the existing methods and can output optimization results at any time. ...
doi:10.1155/2019/1424590
fatcat:lyewpvaxyzef3mkckd6jb7xkku
Multi-objective control chart design optimization using NSGA-III and MOPSO enhanced with DEA and TOPSIS
2016
Expert systems with applications
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to efficiently solve the optimization problem. ...
We applied multi-objective optimization methods founded on the reference-points-based non-dominated sorting genetic algorithm-II (NSGA-III) and a multiobjective particle swarm optimization (MOPSO) algorithm ...
optimization algorithms; (2) utilized different DEA models to find the efficient optimal solutions; and (3) used TOPSIS to further screen provided the high-ranked solutions for a more effective and efficient ...
doi:10.1016/j.eswa.2015.11.007
fatcat:vmxgz25ravcrdfkka7wx62qo2u
An experimental metaheuristic approach for portfolio optimization problem with cardinality constraint
2022
AIP Conference Proceedings
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Cardinality Constrained Portfolio Optimization Problem (CCPOP) is solved using two metaheuristics approaches in this work for a collection of thirty-one assets. ...
Also, the changes in the efficient frontier on varying the value of the cardinality constraint are analyzed. ...
It is evident that the efficient frontier obtained by NSGA-II is close to the UCEF and has more uniformly distributed solutions than MOPSO. ...
doi:10.1063/5.0105712
fatcat:omatrldf5jc3nfn2nqx3r2d3me
Multi Objective PSO with Passive Congregation for Load Balancing Problem
2021
International Journal of Computers Communications & Control
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Multi-Objective Particle Swarm Optimization (MOPSO) based on crowding distance (CD) is a popular MOEA method used to balance HLA load. ...
Hence, it can be a useful tool to optimize the load balancing problem in HLA. ...
However, the major problem arises when the HLA load balance is not optimized when the HLA goes through a large operation and therefore, shows low efficiency. ...
doi:10.15837/ijccc.2021.5.4274
fatcat:pmojtr656jhhbkummt3hnjjokm
Comparison of Service Selection Algorithms for Grid Services: Multiple Objective Particle Swarm Optimization and Constraint Satisfaction Based Service Selection
2008
2008 20th IEEE International Conference on Tools with Artificial Intelligence
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Grid computing has emerged as a global platform to support organizations for coordinated sharing of distributed data, applications, and processes. ...
This paper, proposes and compares two service selection algorithms on the Grid: the Multiple Objective Particle Swarm Optimization algorithm using Crowding Distance technique (MOPSO-CD) to the Constraint ...
The authors wish to acknowledge NSERC (Natural Sciences and Engineering Research Council), for partly fund-ing this research work. ...
doi:10.1109/ictai.2008.16
dblp:conf/ictai/GuhaL08
fatcat:vbzxbz6rbzfifezlrkzaiymxjy
AN OPTIMAL COMPOSITION PLAN SELECTION USING MULTI OBJECTIVE PARTICLE SWARM OPTIMIZATION
2019
INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING & TECHNOLOGY
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It is solved by introducing a Multi-Objective Genetic Algorithm (MOGA) and Multi-Objective PSO (MOPSO) algorithm. ...
While adding a greater number of QoS parameters there will be multi-objective services composition optimization problem. ...
For more efficient automatic web service composition adding few more QoS parameters is considered which optimally select the composition plan. ...
doi:10.34218/ijcet.10.1.2019.024
fatcat:6os7tkzzobafrdlthkvcrqulwu
Multi-Objective Particle Swarm Optimization (MOPSO) based on Pareto Dominance Approach
2014
International Journal of Computer Applications
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This paper presents a comprehensive review of a multiobjective particle swarm optimization (MOPSO) reported in the specialized literature. ...
One of them is multi-objective optimization. Multi-objective optimization is a class of problems with solutions that can be evaluated along two or more incomparable or conflicting objectives. ...
Such as Emphasis on Efficiency, Self-Adaptation of Parameters in MOPSOs, Theoretical Developments and Application Work. ...
doi:10.5120/18738-9983
fatcat:u3chlbmtsbhz3mhslmhdm6ovom
Energy-efficient clustering in mobile ad-hoc networks using multi-objective particle swarm optimization
2012
Applied Soft Computing
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Keywords: Mobile ad hoc network (MANET) Multi-objective particle swarm optimization (MOPSO) Clustering Cluster-head (CH) Energy-efficient networks Load balance factor a b s t r a c t A mobile ad hoc network ...
Clustering involves the selection of cluster-heads (CHs) for each cluster and fewer CHs result in greater energy efficiency as these nodes drain more power than noncluster-heads. ...
The authors are also thankful to the anonymous reviewers for their valuable suggestions and feedback. ...
doi:10.1016/j.asoc.2011.05.036
fatcat:dse23uy5zrdulpbkvujv2szfeu
A novel hybrid teaching learning based multi-objective particle swarm optimization
2017
Neurocomputing
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., Fleming, P.J. orcid.org/0000-0001-9837-8404 et al. (2 more authors) (2017) A novel hybrid teaching learning based multi-objective particle swarm optimization. ...
Shaojun Gan would like to thank the China Scholarship council for financially support their study in UK. ...
Introduction Multi-objective optimization (MOO) problem is presented in a great variety of real-life optimization problems with more than one conflict objectives. ...
doi:10.1016/j.neucom.2016.10.001
fatcat:wu2rm5p6fbfgxd6g4f4aehk5q4
A Novel Ranking-based Optimal Guides Selection Strategy in MOPSO
2016
Procedia Computer Science
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A challenging issue with multi-objective particle swarm optimization (MOPSO) is the mechanism to select the optimal guides. ...
On the basis of ranking, we propose a new maintenance strategy for updating the external archive which can obtain a more diverse and uniform distribution. ...
in objective space, we put forward a new optimal guides selection strategy and apply it to the MOPSO. ...
doi:10.1016/j.procs.2016.07.135
fatcat:6dpphlv7lzf47ekrbmezvj3bxa
Green Clustering Implementation Based on DPS-MOPSO
2014
Mathematical Problems in Engineering
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Particle Swarm Optimization (DPS-MOPSO). ...
A green clustering implementation is proposed to be as the first method in the framework of an energy-efficient strategy for centralized enterprise high-density WLANs. ...
A. in our previous work is implemented through the modified EA. In this paper, a much more time-efficient algorithm DPS-MOPSO is employed. ...
doi:10.1155/2014/721718
fatcat:cxmugfoqazbtpepohmwdcuuasu
Optimal design of dampers in seismic applications utilizing the MOPSO algorithm
2022
Frontiers in Built Environment
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This research proposes a method for the optimal design of viscous dampers in seismic applications utilizing the multi-objective particle swarm optimization (MOPSO) algorithm. ...
New technological developments in engineering present an opportunity for improved efficiency in structural design through optimization. ...
In comparison, the MOPSO algorithm is more computationally efficient as it requires a relatively small number of starting populations to find a global minimum while avoiding trapping in the local optimal ...
doi:10.3389/fbuil.2022.1040129
fatcat:kkob4jgy65e47irzjqqp47gqwq
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