Dynamic Crowding Distance?A New Diversity Maintenance Strategy for MOEAs

Luo, Biao; Zheng, Jinhua; Xie, Jiongliang; Wu, Jun

doi:10.1109/icnc.2008.532

Cited by 85 publications

(62 citation statements)

References 10 publications

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“…If the basement CD is applied, individuals that can help to maintain a uniform spread are removed. To overcome the drawback of NSGA-II, a dynamic crowding distance (DCD) is introduced as described in [25]. Above all, the biggest difference between CD and DCD is that CD is just calculated once, but DCD is varied during the selection of offspring generation:…”

Section: Dynamic Crowding Distancementioning

confidence: 99%

Multi-Objective Scheduling Optimization Based on a Modified Non-Dominated Sorting Genetic Algorithm-II in Voltage Source Converter−Multi-Terminal High Voltage DC Grid-Connected Offshore Wind Farms with Battery Energy Storage Systems

Kim

2017

Energies

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Improving the performance of power systems has become a challenging task for system operators in an open access environment. This paper presents an optimization approach for solving the multi-objective scheduling problem using a modified non-dominated sorting genetic algorithm in a hybrid network of meshed alternating current (AC)/wind farm grids. This approach considers voltage and power control modes based on multi-terminal voltage source converter high-voltage direct current (MTDC) and battery energy storage systems (BESS). To enhance the hybrid network station performance, we implement an optimal process based on the battery energy storage system operational strategy for multi-objective scheduling over a 24 h demand profile. Furthermore, the proposed approach is formulated as a master problem and a set of sub-problems associated with the hybrid network station to improve the overall computational efficiency using Benders' decomposition. Based on the results of the simulations conducted on modified institute of electrical and electronics engineers (IEEE-14) bus and IEEE-118 bus test systems, we demonstrate and confirm the applicability, effectiveness and validity of the proposed approach.

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Section: Dynamic Crowding Distancementioning

confidence: 99%

Multi-Objective Scheduling Optimization Based on a Modified Non-Dominated Sorting Genetic Algorithm-II in Voltage Source Converter−Multi-Terminal High Voltage DC Grid-Connected Offshore Wind Farms with Battery Energy Storage Systems

Kim

2017

Energies

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“…The major drawback of crowding distance is the lack of uniform diversity in obtained nondominated solutions. To overcome this problem, DCD method is suggested in [35]. The DCD of individuals is calculated based on…”

Section: Dynamic Crowding Distance (Dcd) Algorithmmentioning

confidence: 99%

Multiobjective Optimization for Topology and Coverage Control in Wireless Sensor Networks

Jameii

Faez

Dehghan

2015

International Journal of Distributed Sensor Networks

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Coverage, connectivity, and network lifetime are important issues in wireless sensor networks (WSNs). Balancing the energy consumption in the network, reducing the transmission range of nodes, and density control of active nodes are approaches to extend the network lifetime. However, transmission range reduction and smaller number of active nodes can affect the network topology and may cause the network to be disconnected. So, there exist conflicts among lifetime, coverage, and connectivity. In this paper, these conflicting issues are considered and an evolutionary multiobjective optimization approach based on nondominated sorting genetic algorithm-II (NSGA-II) is proposed to optimize them. Simulation results demonstrate that the proposed algorithm can improve the network lifetime and coverage while maintaining the network connectivity.

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“…In order to improve the diversity of the external archive, this paper employs a diversity maintenance strategy (DMS) based on dynamic crowding distance (DCD) [35], a revised version of crowding distance (CD) proposed in NSGA-II. The DCD of the individual is given as follows:…”

Section: Dynamic Crowding Distancementioning

confidence: 99%

Application of Hybrid MOPSO Algorithm to Optimal Reactive Power Dispatch Problem Considering Voltage Stability

Zeng

Sun

2014

Journal of Electrical and Computer Engineering

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This study presents a novel hybrid multiobjective particle swarm optimization (HMOPSO) algorithm to solve the optimal reactive power dispatch (ORPD) problem. This problem is formulated as a challenging nonlinear constrained multiobjective optimization problem considering three objectives, that is, power losses minimization, voltage profile improvement, and voltage stability enhancement simultaneously. In order to attain better convergence and diversity, this work presents the use of combing the classical MOPSO with Gaussian probability distribution, chaotic sequences, dynamic crowding distance, and self-adaptive mutation operator. Moreover, multiple effective strategies, such as mixed-variable handling approach, constraint handling technique, and stopping criteria, are employed. The effectiveness of the proposed algorithm for solving the ORPD problem is validated on the standard IEEE 30-bus and IEEE 118-bus systems under nominal and contingency states. The obtained results are compared with classical MOPSO, nondominated sorting genetic algorithm (NSGA-II), multiobjective evolutionary algorithm based on decomposition (MOEA/D), and other methods recently reported in the literature from the point of view of Pareto fronts, extreme, solutions and multiobjective performance metrics. The numerical results demonstrate the superiority of the proposed HMOPSO in solving the ORPD problem while strictly satisfying all the constraints.

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Dynamic Crowding Distance?A New Diversity Maintenance Strategy for MOEAs

Cited by 85 publications

References 10 publications

Multi-Objective Scheduling Optimization Based on a Modified Non-Dominated Sorting Genetic Algorithm-II in Voltage Source Converter−Multi-Terminal High Voltage DC Grid-Connected Offshore Wind Farms with Battery Energy Storage Systems

Multi-Objective Scheduling Optimization Based on a Modified Non-Dominated Sorting Genetic Algorithm-II in Voltage Source Converter−Multi-Terminal High Voltage DC Grid-Connected Offshore Wind Farms with Battery Energy Storage Systems

Multiobjective Optimization for Topology and Coverage Control in Wireless Sensor Networks

Application of Hybrid MOPSO Algorithm to Optimal Reactive Power Dispatch Problem Considering Voltage Stability

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