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  A Novel Genetic Algorithm Optimized Adversarial Attack in Federated Learning for Android-Based Mobile Systems 

  Nawshin, Faria; Unal, Devrim; Hammoudeh, Mohammad; Suganthan, Ponnuthurai N. ( Institute of Electrical and Electronics Engineers (IEEE) , 2025 , Article)

  Federated Learning (FL) is gaining traction in Android-based consumer electronics, enabling collaborative model training across decentralized devices while preserving data privacy. However, the increasing adoption of FL ...
• Shipping economic forecasting: recent developments, applications, and future directions 

  Mo, Jixian; Gao, Ruobin; Yuen, Kum Fai; Suganthan, Ponnuthurai Nagaratnam ( Taylor and Francis , 2025 , Article)

  Forecasting is vital in shipping economics and directly affects the business decisions of shipping companies and the quality development of the shipping markets. This study critically reviews variables, methods, and results ...
• Reinforcement Learning Assisting Artificial Bee Colony Algorithm for Scheduling Distributed Assembly Flowshops With Batch Delivery 

  Li, Dachao; Gao, Kaizhou; Duan, Peiyong; Suganthan, Ponnuthurai N.; Wu, Naiqi ( Institute of Electrical and Electronics Engineers (IEEE) , 2025 , Article)

  In response to escalating market demands, we extend the distributed assembly flowshop problems (DAFSPs) by incorporating batch delivery, optimizing both total energy consumption (TEC) and total completion time, simultaneously. ...
• Dynamic economic dispatch of multi-area wind-solar-thermal power systems with fractional order comprehensive learning differential evolution 

  Xiong, Guojiang; Xu, Shengping; Suganthan, Ponnuthurai Nagaratnam; Wang, Yang ( Elsevier , 2025 , Article)

  The significance of multi-area dynamic economic dispatch (MADED) is amplified by the integration of wind and solar energy sources which introduces considerable fluctuations. In this work, a MADED model incorporating wind ...
• Economic emission dispatch of power systems considering uncertainty of wind-solar-hydro with fractional order multi-objective differential evolution 

  Xiong, Guojiang; Suganthan, Ponnuthurai Nagaratnam; Guo, Hanhao ( Elsevier , 2025 , Article)

  The integration of renewable energy brings significant uncertainty to the operation of power systems. Multi-objective economic emission dispatch (MOEED) becomes an important way to reduce operating costs and emissions under ...
• Auxiliary population-assisted differential evolution for multi-area economic dispatch considering valve point effects 

  Xiong, Guojiang; Liu, Jiazeng; Du, Zhengjie; Suganthan, Ponnuthurai Nagaratnam; Shi, Xin ( Elsevier , 2025 , Article)

  Multi-area economic dispatch (MAED) is an indispensable task in the power system's operation. Nevertheless, the valve point effects of generating units make the problem highly nonlinear and non-convex. In this paper, a ...
• A review on metaheuristics for solving home health care routing and scheduling problems 

  Dong, Jie; Gao, Kaizhou; Suganthan, Ponnuthurai Nagaratnam; Huang, Min; Zhu, Lihua; Fu, Yaping... more authors ... less authors ( Elsevier , 2025 , Article)

  Nowadays, the healthcare of elderly people catches wide attention since the increase of aging population puts significant pressure on public medical resources. The population aging and scarce care resources are likely to ...
• Beyond a single solution: Liquefied natural gas process optimization using niching-enhanced meta-heuristics 

  Gaben, Shahd; Al-Saadi, Abdullah; Al-Ali, Abdulaziz; Khraisheh, Majeda; Almomani, Fares; Suganthan, Ponnuthurai N.; Hamdy, Mohamed... more authors ... less authors ( Elsevier , 2025 , Article)

  The escalating global energy demand and the imperative to mitigate climate change necessitate optimizing the natural gas liquefaction process to enhance energy efficiency, reduce costs, and improve sustainability. Traditional ...
• Bayesian forward regularization replacing Ridge in online randomized neural network with multiple output layers 

  Hu, Minghui; Li, Ning; Suganthan, Ponnuthurai Nagaratnam; Wang, Junda ( Elsevier , 2025 , Article)

  Forward regularization (-F) with unsupervised knowledge was advocated to replace canonical Ridge regularization (-R) in online linear learners, as it achieved a lower relative regret boundary. However, we observe that -F ...
• Drone on-demand delivery routing problem considering order splitting and battery swapping 

  Shuxuan, Li; Liao, Tianjun; Wu, Guohua; Wang, Yalin; Suganthan, Ponnuthurai Nagaratnam ( Elsevier , 2025 , Article)

  The use of drone delivery has catalyzed technological innovation within the logistics industry. This delivery mode can reduce on-demand delivery times by up to 50 %, while also significantly lowering labor costs and ...
• Learning strategies for particle swarm optimizer: A critical review and performance analysis 

  Dikshit, Chauhan; Shivani; Suganthan, Ponnuthurai N. ( Elsevier , 2025 , Article)

  Nature has long inspired the development of swarm intelligence (SI), a key branch of artificial intelligence that models collective behaviors observed in biological systems for solving complex optimization problems. Particle ...
• A comprehensive survey of adaptive strategies in differential evolutionary algorithms 

  Li, Jianping; Wang, Peng; Suganthan, Ponnuthurai Nagaratnam; Ye, Xinggui ( Elsevier , 2025 , Article)

  Classical differential evolution (DE) encounters premature convergence when dealing with diverse optimization problems. This challenge has encouraged extensive research efforts aimed at improving and enhancing the original ...
• A reinforcement learning-assisted genetic programming algorithm for team formation problem considering person-job matching 

  Wang, Hao; He, Lei; Pedrycz, Witold; Suganthan, Ponnuthurai Nagaratnam; Xing, Lining; Song, Yanjie; Guo, Yangyang... more authors ... less authors ( Elsevier , 2025 , Article)

  Efficient team formation is crucial for successful completion of new projects in a company. To address the team formation problem considering person-job matching (TFP-PJM), a 0-1 integer programming model with intuitionistic ...
• Carbon footprint of global Bitcoin mining: emissions beyond borders 

  Cihat Onat, Nuri Cihat; Jabbar, Rateb; Kucukvar, Murat; Wakjira, Tadesse; Kutty, Adeeb A.; Fetais, Noora... more authors ... less authors ( Springer , 2025 , Article)

  Executing a single Bitcoin transaction equates approximately to the greenhouse gas emissions of a moderate-sized electric or gasoline engine sedan vehicle traveling between 1600 and 2600 km. This research undertakes an ...
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  Insects in agricultural greenhouses: a metagenomic analysis of microbes in Trialeurodes vaporariorum infesting tomato and cucumber crops 

  Qush, Abeer; Assaad, Nada; Alkhayat, Fatima Abdulla; Al-Kuwari, Mohammed Saif; Al-Khalaf, Nasser; Bassil, Maya S.; Yassine, Hadi M.; Zeidan, Asad; Razali, Rozaimi Mohamad; Kamareddine, Layla... more authors ... less authors ( Frontiers Media SA , 2025 , Article)

  Introduction: With the predicted 9-10 billion world population increase by 2050 and its accompanying need for sustainable food production, and with the harsh climate conditions challenging agriculture and food security in ...
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  Class-incremental Learning for Time Series: Benchmark and Evaluation 

  Qiao, Zhongzheng; Pham, Quang; Cao, Zhen; Le, Hoang H.; Suganthan, P. N.; Jiang, Xudong; Ramasamy, Savitha... more authors ... less authors ( Association for Computing Machinery (ACM) , 2024 , Conference)

  Real-world environments are inherently non-stationary, frequently introducing new classes over time. This is especially common in time series classification, such as the emergence of new disease classification in healthcare ...
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  Vanilla Gradient Descent for Oblique Decision Trees 

  Panda, Subrat Prasad; Genest, Blaise; Easwaran, Arvind; Suganthan, Ponnuthurai Nagaratnam ( IOS Press , 2024 , Conference)

  Decision Trees (DTs) constitute one of the major highly non-linear AI models, valued, e.g., for their efficiency on tabular data. Learning accurate DTs is, however, complicated, especially for oblique DTs, and does take a ...
• An archive-assisted multi-modal multi-objective evolutionary algorithm 

  Peng, Chen; Li, Zhimeng; Qiao, Kangjia; Suganthan, P.N.; Ban, Xuanxuan; Yu, Kunjie; Yue, Caitong; Liang, Jing... more authors ... less authors ( Elsevier , 2024 , Article)

  The multi-modal multi-objective optimization problems (MMOPs) pertain to characteristic of the decision space that exhibit multiple sets of Pareto optimal solutions that are either identical or similar. The resolution of ...
• Energy-efficient multi-objective distributed assembly permutation flowshop scheduling by Q-learning based meta-heuristics 

  Hui, Yu; Gao, Kaizhou; Li, Zhiwu; Suganthan, Ponnuthurai Nagaratnam ( Elsevier , 2024 , Article)

  This study addresses energy-efficient multi-objective distributed assembly permutation flowshop scheduling problems with minimisation of maximum completion time, mean of earliness and tardiness, and total carbon emission ...
• A staged fuzzy evolutionary algorithm for constrained large-scale multiobjective optimization 

  Jinlong, Zhou; Zhang, Yinggui; Yu, Fan; Yang, Xu; Suganthan, Ponnuthurai Nagaratnam ( Elsevier , 2024 , Article)

  Constrained multiobjective optimization problems (CMOPs) are prevalent in practical applications, where constraints play a significant role. Building on techniques from constrained single-objective optimization, classical ...

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