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Article
Computer Science, Interdisciplinary Applications
Qian Fan et al.
Summary: This paper proposes a hybrid meta-heuristic algorithm called ESSAWOA for solving global optimization problems. ESSAWOA combines the mechanisms of SSA and LOBL to enhance WOA, resulting in improved exploitation and exploration capacity. The experimental results demonstrate that ESSAWOA outperforms basic WOA, SSA, and other meta-heuristic algorithms in solving optimization problems effectively and efficiently.
ENGINEERING WITH COMPUTERS
(2022)
Article
Computer Science, Artificial Intelligence
Wei Xu et al.
Summary: The Crow Search Algorithm (CSA) has limitations due to crows learning from only one goal. To address this issue, an improved algorithm called OFLCSA is proposed in this paper, which combines forgetting mechanism and opposition-based learning strategy, along with elite crow and adaptive flight length to enhance performance.
APPLIED INTELLIGENCE
(2022)
Article
Computer Science, Artificial Intelligence
Jing Liu et al.
Summary: While the concept of swarm intelligence was introduced in the 1980s, the first swarm optimisation algorithm was not introduced until 1992. Analyzing nineteen original swarm optimisation algorithms revealed that while state-of-the-art algorithms are competitive in finding solutions, they are more computationally demanding compared to the original algorithms.
ARTIFICIAL INTELLIGENCE REVIEW
(2022)
Article
Computer Science, Artificial Intelligence
Fuqiang Lu et al.
Summary: IT outsourcing plays a crucial role in helping enterprises improve competitiveness and reduce costs, but schedule risks must be carefully managed. A bi-level multi-objective schedule risk management model is established, along with a bi-level Whale Optimization Algorithm to effectively control schedule risks in IT outsourcing projects. The algorithm demonstrates competitive accuracy and the ability to avoid local optima.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Automation & Control Systems
Peng Chen et al.
Summary: This paper proposes a novel bio-inspired algorithm, TQA, which solves optimization problems by simulating the division of labor in termite populations. TQA is tested on benchmark functions and applied to real world engineering design problems, demonstrating its reliability and effectiveness in solving global optimization problems and engineering design problems.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Computer Science, Artificial Intelligence
Yongliang Yuan et al.
Summary: This paper proposes a novel assisted optimization strategy, EOCS, for tackling highly non-linear optimization problems. By combining the elite opposition-based learning strategy and chaotic k-best gravitational search strategy, the proposed method demonstrates competitive accuracy and robustness, ranking first among the compared optimization algorithms.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Interdisciplinary Applications
Jianxun Liu et al.
Summary: The Whale optimization algorithm (WOA) suffers from weak exploration ability, poor convergence behavior, and a tendency to fall into local optima. To address these issues, this study analyzes WOA from the perspectives of global exploration efficiency and convergence characteristics, and proposes population redistribution and convergent adaptive weighting strategies. Experimental results demonstrate that these strategies effectively enhance the exploration efficiency and convergence behavior of WOA. The Reinforced Exploration Mechanism Whale Optimization Algorithm (REM-WOA) shows advantages over other meta-heuristic algorithms and achieves the best exploration efficiency in three real design case studies.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2022)
Article
Computer Science, Artificial Intelligence
Pingfan Xia et al.
Summary: This study proposes a novel bio-inspired algorithm, called dynamic evolutionary glowworm swarm optimisation (DEGSO), for optimizing the parameters of long short-term memory (LSTM) in money laundering risk prediction. Experimental results demonstrate that this method outperforms other approaches in terms of performance and achieves satisfactory results in money laundering risk prediction.
INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION
(2022)
Article
Mathematical & Computational Biology
Rong Zheng et al.
Summary: This paper presents an improved Arithmetic Optimization Algorithm (IAOA) integrated with a proposed Forced Switching Mechanism (FSM) to address the limitations of the original AOA. Experimental results demonstrate that the proposed algorithm outperforms other comparative algorithms in handling various problems.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Alexandros Tzanetos et al.
Summary: In the last decade, there has been a rise in nature-inspired optimization algorithms, but some of them lack true inspiration from nature or practical application, leading to potential drawbacks. This study highlights findings from existing nature-inspired algorithms and suggests guidelines for developing new algorithms.
ARTIFICIAL INTELLIGENCE REVIEW
(2021)
Article
Computer Science, Artificial Intelligence
Yongjun Sun et al.
Summary: MIWOA is proposed to enhance the performance of WOA in tackling high dimensional optimization problems. It introduces multi-population exploitation and exploration processes, improves learning process, and uses interpolation method to enhance search ability near the current optimum. Additionally, a control parameter is used to balance exploitation and exploration processes. Simulation results show that MIWOA outperforms other algorithms in solution accuracy, convergence speed, and execution time.
APPLIED SOFT COMPUTING
(2021)
Article
Engineering, Industrial
Adel Aazami et al.
Summary: This paper develops a new multi-period production-distribution planning for perishable products in a seller-buyer system, optimizing the seller's profit in a three-level supply chain. It includes cooperative actions between factories and distribution centers, a vertical competition involving retailers, and strategies to encourage retailers. The proposed hierarchical heuristic approach shows efficient performance in solving the NP-hard problem.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Computer Science, Information Systems
Sushmita Sharma et al.
Summary: A novel hybrid BOA algorithm, MPBOA, is proposed in this paper, combining the exploration and exploitation characteristics of BOA with mutualism and parasitism phases of the SOS algorithm. The algorithm shows satisfactory performance in terms of search behavior and convergence time on twenty-five benchmark functions.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Juan F. Farfan et al.
Summary: The study proposes a method combining swarm intelligence optimization with artificial neural network-based surrogate model for hydrological model calibration. Results show that the proposed method achieves an accuracy rate of 89-99% in identifying suitable parameter sets and reduces CPU time significantly compared to standard implementations.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Sanjoy Chakraborty et al.
Summary: The Whale Optimization Algorithm was developed based on the prey-catching characteristics of humpback whales and has been widely used in various disciplines due to its simplicity and efficiency. However, it has been found to have limitations in exploration ability, accuracy, and convergence in high-dimensional optimization problems. This study introduces a new variant with modifications to address these issues and enhance the algorithm's performance by balancing global and local search phases, modifying co-efficient vectors, and introducing random movement. The proposed algorithm demonstrates better performance on higher-dimensional problems compared to the basic Whale Optimization Algorithm and its variants.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Sanjoy Chakraborty et al.
Summary: An enhanced Whale Optimization Algorithm (WOAmM) is proposed in this work to overcome premature convergence issues by modifying the mutualism phase, leading to more comprehensive exploration of the search space. The method demonstrates improved performance and superiority over other algorithms in testing.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Mohammad H. Nadimi-Shahraki et al.
Summary: An Improved Grey Wolf Optimizer (I-GWO) is proposed in this article to tackle global optimization and engineering design problems by introducing a dimension learning-based hunting (DLH) search strategy. The IGWO algorithm addresses the lack of population diversity, imbalance between exploitation and exploration, and premature convergence seen in the GWO algorithm. Experimental results show that I-GWO is competitive against six other state-of-the-art metaheuristics, demonstrating its efficiency and applicability in engineering design problems.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Absalom E. Ezugwu et al.
Summary: Research in metaheuristics for global optimization problems is advancing rapidly with an exponential growth of new generation algorithms. These algorithms prioritize novelty over performance. Researchers should track the progress of these algorithms and understand their design profiles and applications.
ARTIFICIAL INTELLIGENCE REVIEW
(2021)
Article
Computer Science, Interdisciplinary Applications
Vincent F. Yu et al.
Summary: This paper addresses the heterogeneous fleet vehicle routing problem with multiple cross-docks and proposes a mixed integer linear program and adaptive neighborhood simulated annealing algorithm for solving it. Results of computational study demonstrate the excellent performance of the proposed algorithm in terms of solution quality and computational efficiency.
COMPUTERS & OPERATIONS RESEARCH
(2021)
Review
Automation & Control Systems
Jun Tang et al.
Summary: Swarm intelligence algorithms are a subset of artificial intelligence that has gained popularity for solving optimization problems and has been widely utilized in various applications. This review summarizes the most representative swarm intelligence algorithms and their successful applications in engineering fields, providing insights into future trends and prospects for development.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2021)
Article
Computer Science, Artificial Intelligence
Xian-fang Song et al.
Summary: The paper proposes a novel feature selection algorithm based on bare bones PSO with mutual information, achieving better performance. The algorithm enhances exploitation performance through effective swarm initialization strategy and local search operators, while also designing an adaptive flip mutation operator.
PATTERN RECOGNITION
(2021)
Article
Environmental Studies
Xiaolei Zheng et al.
Summary: This study explored the relationship between production factors, ore grades, and life of mine to forecast mining capital cost (MCC) for open pit mining projects. The developed SalpSO-CFNN model showed good accuracy with a mean absolute error of 179.567, root-mean-squared error of 248.401, and determination coefficient of 0.980, outperforming other benchmark models. Sensitivity analysis indicated that MineAP and MillAP were the most influential parameters on the forecast of MCC.
Article
Business, Finance
Hao Zhang et al.
Summary: This paper utilized the firefly algorithm support vector machine (FA-SVM) for supply chain financial evaluation, selected appropriate indicators for accurate credit risk assessment, and demonstrated the improvement in classification prediction compared to LIBSVM.
RESEARCH IN INTERNATIONAL BUSINESS AND FINANCE
(2021)
Article
Computer Science, Artificial Intelligence
Zhuhong Zhang et al.
Summary: The fly visual evolutionary neural network combines features of fly visual perception and swarm evolution to solve large-scale global optimization problems. It consists of two functional modules, one for generating neural node motion direction activities and the other for updating node states to optimize the structure of a multilayer perceptron. Experimental results show that the network is an effective optimizer for large-scale global optimization problems.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Zheping Yan et al.
Summary: The enhanced whale optimization algorithm adopts the Levy flight strategy and ranking-based mutation operator to overcome the drawbacks of the basic algorithm, achieving a balanced exploration and exploitation to improve search performance.
MATHEMATICS AND COMPUTERS IN SIMULATION
(2021)
Article
Green & Sustainable Science & Technology
Gurcan Cetin et al.
Summary: This article discusses the application of the Simulated Annealing (SA) algorithm for optimizing the performance of a binary geothermal power plant in Turkey and compares it to the Gravitational Search Algorithm (GSA). The study results show that the SA algorithm outperforms the GSA algorithm and can improve the efficiency of the power plant.
Article
Computer Science, Interdisciplinary Applications
Suyanto Suyanto et al.
Summary: This paper introduces an evolutionary Rao algorithm (ERA) with two new schemes and evolutionary operators to enhance performance and convergence speed. The fitness-based adaptation effectively controls the exploitation-exploration balance by dynamically tuning parameters throughout the evolution process, leading to improved results compared to competitors.
JOURNAL OF COMPUTATIONAL SCIENCE
(2021)
Article
Computer Science, Information Systems
Jingyi Liu et al.
Summary: The improved grey wolf optimization algorithm (IGWO) integrates the lion optimizer algorithm and dynamic weights into the original grey wolf optimization algorithm. Experimental results show that the algorithm effectively improves accuracy and convergence speed, with better optimization effects.
Article
Computer Science, Information Systems
Yousef Hassouneh et al.
Summary: In this study, an enhanced version of the Whale Optimization Algorithm (WOA) is proposed for software fault prediction, combined with a single point crossover method. Through deep analysis of 17 SFP datasets, it is found that the proposed approach outperforms the original WOA and other six state-of-the-art methods, as well as enhances the overall performance of the machine learning classifier.
Review
Computer Science, Information Systems
Sourabh Katoch et al.
Summary: This paper discusses recent advances in genetic algorithms, analyzing selected algorithms of interest in the research community. It helps new and demanding researchers gain a broader understanding of genetic algorithms. The review covers well-known algorithms, genetic operators, research domains, and future research directions in genetic algorithms.
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JOURNAL OF CLEANER PRODUCTION
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Article
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SCIENCE OF THE TOTAL ENVIRONMENT
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Review
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NEURAL COMPUTING & APPLICATIONS
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Yangming Zhou et al.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
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(2014)
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