Lévy Flight Trajectory-Based Whale Optimization Algorithm for Global Optimization

Liu, Ying; Zhou, Yongquan; Luo, Qifang

doi:10.1109/access.2017.2695498

Cited by 350 publications

(153 citation statements)

References 29 publications

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“…The Whale Optimization Algorithm (WOA) is a developed swarm-based optimization technique for solving optimization problems in many applications [51][52][53][54][55][56][57][58][59]. WOA is a meta-heuristic algorithm, which is first introduced and developed by Mirjalili and Lewis in 2016.…”

Section: Wot Overview and Methodologymentioning

confidence: 99%

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A Reconfigured Whale Optimization Technique (RWOT) for Renewable Electrical Energy Optimal Scheduling Impact on Sustainable Development Applied to Damietta Seaport, Egypt

et al. 2018

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This paper studies the effect on the rate of growth of carbon dioxide emission in seaports' atmosphere of replacing a part of the fossil fuel electrical power generation by clean renewable electrical energies, through two different scheduling strategies. The increased rate of harmful greenhouse gas emissions due to conventional electrical power generation severely affects the whole global atmosphere. Carbon dioxide and other greenhouse gases emissions are responsible for a significant share of global warming. Developing countries participate in this environmental distortion to a great percentage. Two different suggested strategies for renewable electrical energy scheduling are discussed in this paper, to attain a sustainable green port by the utilization of two mutual sequential clean renewable energies, which are biomass and photovoltaic (PV) energy. The first strategy, which is called the eco-availability mode, is a simple method. It is based on operating the renewable electrical energy sources during the available time of operation, taking into consideration the simple and basic technical issues only, without considering the sophisticated technical and economical models. The available operation time is determined by the environmental condition. This strategy is addressed to result on the maximum available Biomass and PV energy generation based on the least environmental and technical conditions (panel efficiency, minimum average daily sunshine hours per month, minimum average solar insolation per month). The second strategy, which is called the Intelligent Scheduling (IS) mode, relies on an intelligent Reconfigured Whale Optimization Technique (RWOT) based-model. In this strategy, some additional technical and economical issues are considered. The studied renewable electrical energy generation system is considered in two scenarios, which are with and without storage units. The objective (cost) function of the scheduling optimization problem, for both scenarios, are developed. Also, the boundary conditions and problem constraints are concluded. The RWOT algorithm is an updated Whale Optimization Algorithm (WOA). It is developed to accelerate the rate of reaching the optimal solution for the IS problem. The two strategies simulation and implementation are illustrated and applied to the seaport of Damietta, which is an Egyptian port, located 10 km to the west of the Nile River (Damietta Branch). The scheduling of PV and biomass energy generation during the different year months is examined for both strategies. The impact of renewable electrical energies generation scheduling on carbon dioxide emission and consequently global warming is discussed. The saving in carbon dioxide emission is calculated and the efficient results of the suggested models are clarified. The carbon dioxide emission is reduced to around its fifth value, during renewable energy operation. This work focuses on decreasing the rate of growth of carbon dioxide emission coming from fossil fuel electrical power generation in Egypt, targ...

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Section: Wot Overview and Methodologymentioning

confidence: 99%

“…An overview of statistical performance evaluation for different evolutionary algorithms is studied [51][52][53][54][55][56][57][58][59]. Comprehensive simulations and statistical analysis are implemented on different algorithm (WOA, PSO and GA) for different standard test functions, showing that:…”

Section: Search For Prey (Exploration Phase)mentioning

confidence: 99%

A Reconfigured Whale Optimization Technique (RWOT) for Renewable Electrical Energy Optimal Scheduling Impact on Sustainable Development Applied to Damietta Seaport, Egypt

et al. 2018

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“…15 Oliva et al enhanced WOA by combining it with chaotic maps that are used for better estimating the parameters of Photo-Voltaic (PV) cells using circuit models. 19 Abdel-Basset et al 20 Merkle-Hellman public key cryptosystem. 17 Dao et al proposed a planning algorithm used for optimizing mobile robot path planning problems 18 ; the algorithm is based on a multi-objective approach and is integrated with WOA.…”

mentioning

confidence: 99%

“…Ling et al applied Lévy flight trajectory to WOA for enhancing its precision in finding best global optima and convergence rate. 19 Abdel-Basset et al 20 integrated WOA based algorithm with Cloudsim toolkit to competently solve the virtual machine placement problem in cloud computing. Zhang et al 21 demonstrated the use of WOA for synthesis of linear antenna arrays, which are widely used in radar, communications, remote sensing, and in many other fields.…”

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confidence: 99%

Distributed Whale Optimization Algorithm based on MapReduce

Khalil

Alshayeji

Ahmad

2018

Concurrency and Computation

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Whale Optimization Algorithm (WOA) is a recent swarm intelligence based meta-heuristic optimization algorithm, which simulates the natural behavior of bubble-net hunting strategy of humpback whales and has been successfully applied to solve complex optimization problems in a wide range of disciplines. However, when applied to large-size problems, its performance degrades due to the need of massive computational work load. Distributed computing is one of the effective ways to improve the scalability of WOA for solving large-scale problems. In this paper, we propose a simple and robust distributed implementation of WOA using Hadoop MapReduce named MR-WOA. MapReduce paradigm is adopted as the distribution model since it is one of the most mature technologies to develop parallel algorithms which automatically handles communication, load balancing, data locality, and fault tolerance. The design of MR-WOA is discussed in details using the MapReduce paradigm. Experiments are conducted for a set of well-known benchmarks for evaluating the quality, speedup, and scalability of MR-WOA. The conducted experiments reveal that our approach achieves a promising speedup. For some benchmarks, speedup scales linearly with increasing the number of computational nodes.

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“…For instance, Trivedi et al [8] proposed an improved version of WOA (called AWOA) based on modified position-updated equation. Ling et al [9] developed an improved version of WOA (called LWOA) with Levy flight trajectory to make faster convergence and avoid premature convergence. Hu et al [10] presented an improved version of WOA (called IWOA) based on inertia weight.…”

Section: Introductionmentioning

confidence: 99%

Whale optimization algorithm with nonlinear control parameter

Zhong

Long

2017

MATEC Web Conf.

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Abstract. Whale optimization algorithm (WOA) is a relatively novel intelligence optimization technique which has been shown to be competitive to other population-based algorithms. However, the control parameter is a major factor to affect the algorithm's convergence precision and speed. At present, few of a them are aiming at control parameter setting in WOA algorithm. This paper proposes corresponding improved WOA algorithm with different nonlinear adjustment strategy of control parameter by adopting a sinusoid, cosine, tangential, logarithmic and quadratic curves. The experimental results for six benchmark test functions show that the proposed nonlinear adjustment strategies are superior to the classical linear strategy.

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Lévy Flight Trajectory-Based Whale Optimization Algorithm for Global Optimization

Cited by 350 publications

References 29 publications

A Reconfigured Whale Optimization Technique (RWOT) for Renewable Electrical Energy Optimal Scheduling Impact on Sustainable Development Applied to Damietta Seaport, Egypt

A Reconfigured Whale Optimization Technique (RWOT) for Renewable Electrical Energy Optimal Scheduling Impact on Sustainable Development Applied to Damietta Seaport, Egypt

Distributed Whale Optimization Algorithm based on MapReduce

Whale optimization algorithm with nonlinear control parameter

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