Leyu Zheng¹, Mingming Xiao^1,*, Yi Ren², Ke Li¹, Chang Sun¹

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072036 - 12 January 2026

Abstract In a wide range of engineering applications, complex constrained multi-objective optimization problems (CMOPs) present significant challenges, as the complexity of constraints often hampers algorithmic convergence and reduces population diversity. To address these challenges, we propose a novel algorithm named Constraint Intensity-Driven Evolutionary Multitasking (CIDEMT), which employs a two-stage, tri-task framework to dynamically integrates problem structure and knowledge transfer. In the first stage, three cooperative tasks are designed to explore the Constrained Pareto Front (CPF), the Unconstrained Pareto Front (UPF), and the ε-relaxed constraint boundary, respectively. A CPF-UPF relationship classifier is employed to construct a problem-type-aware… More >

Hongyu Wang¹, Wenwu Cui¹, Kai Cui¹, Zixuan Meng^2,*, Bin Li², Wei Zhang¹, Wenwen Li¹

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.069576 - 27 December 2025

Abstract To achieve low-carbon regulation of electric vehicle (EV) charging loads under the “dual carbon” goals, this paper proposes a coordinated scheduling strategy that integrates dynamic carbon factor prediction and multi-objective optimization. First, a dual-convolution enhanced improved Crossformer prediction model is constructed, which employs parallel 1 × 1 global and 3 × 3 local convolution modules (Integrated Convolution Block, ICB) for multi-scale feature extraction, combined with an Adaptive Spectral Block (ASB) to enhance time-series fluctuation modeling. Based on high-precision predictions, a carbon-electricity cost joint optimization model is further designed to balance economic, environmental, and grid-friendly objectives.… More > Graphic Abstract

Muhammad Waqar Khan^1,*, Adnan Ahmed Siddiqui¹, Syed Sajjad Hussain Rizvi²

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-15, 2026, DOI:10.32604/cmc.2025.070858 - 09 December 2025

Abstract The multi-objective optimization problems, especially in constrained environments such as power distribution planning, demand robust strategies for discovering effective solutions. This work presents the improved variant of the Multi-population Cooperative Constrained Multi-Objective Optimization (MCCMO) Algorithm, termed Adaptive Diversity Preservation (ADP). This enhancement is primarily focused on the improvement of constraint handling strategies, local search integration, hybrid selection approaches, and adaptive parameter control. The improved variant was experimented on with the RWMOP50 power distribution system planning benchmark. As per the findings, the improved variant outperformed the original MCCMO across the eleven performance metrics, particularly in terms… More >

Junjun Ren¹, Guoqiang Chen², Zheng-Yi Chai³, Dong Yuan^4,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-26, 2026, DOI:10.32604/cmc.2025.068795 - 10 November 2025

Abstract Vehicle Edge Computing (VEC) and Cloud Computing (CC) significantly enhance the processing efficiency of delay-sensitive and computation-intensive applications by offloading compute-intensive tasks from resource-constrained onboard devices to nearby Roadside Unit (RSU), thereby achieving lower delay and energy consumption. However, due to the limited storage capacity and energy budget of RSUs, it is challenging to meet the demands of the highly dynamic Internet of Vehicles (IoV) environment. Therefore, determining reasonable service caching and computation offloading strategies is crucial. To address this, this paper proposes a joint service caching scheme for cloud-edge collaborative IoV computation offloading. By… More >

Asal Jameel Khudhair^#, Amenah Dahim Abbood^#,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-31, 2026, DOI:10.32604/cmc.2025.068553 - 10 November 2025

Abstract Community detection is one of the most fundamental applications in understanding the structure of complicated networks. Furthermore, it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships. Networking structures are highly sensitive in social networks, requiring advanced techniques to accurately identify the structure of these communities. Most conventional algorithms for detecting communities perform inadequately with complicated networks. In addition, they miss out on accurately identifying clusters. Since single-objective optimization cannot always generate accurate and comprehensive results, as multi-objective optimization can. Therefore, we utilized two objective functions… More >

Rytis Maskeliūnas¹, Robertas Damaševičius^1,*, Audrius Kulikajevas¹, Kipras Pribuišis², Nora Ulozaitė-Stanienė², Virgilijus Uloza²

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.3, pp. 4203-4223, 2025, DOI:10.32604/cmes.2025.072790 - 23 December 2025

Abstract This study introduces a novel voice cloning framework driven by Mordukhovich Subdifferential Optimization (MSO) to address the complex multi-objective challenges of pathological speech synthesis in under-resourced Lithuanian language with unique phonemes not present in most pre-trained models. Unlike existing voice synthesis models that often optimize for a single objective or are restricted to major languages, our approach explicitly balances four competing criteria: speech naturalness, speaker similarity, computational efficiency, and adaptability to pathological voice patterns. We evaluate four model configurations combining Lithuanian and English encoders, synthesizers, and vocoders. The hybrid model (English encoder, Lithuanian synthesizer, English More >

Shuxun Li^1,2, Xinhao Liu^1,2,*, Yu Zhang^1,2, Yu Zhao^1,2

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.10, pp. 2495-2526, 2025, DOI:10.32604/fdmp.2025.068674 - 30 October 2025

Abstract Hydraulic control valves, positioned at the terminus of pipe networks, are critical for regulating flow and pressure, thereby ensuring the operational safety and efficiency of pipeline systems. However, conventional valve designs often struggle to maintain effective regulation across a wide range of system pressures. To address this limitation, this study introduces a novel Pilot hydraulic valves specifically engineered for enhanced dynamic performance and precise regulation under variable pressure conditions. Building upon prior experimental findings, the proposed design integrates a high-fidelity simulation framework and a surrogate model-based optimization strategy. The study begins by formulating a comprehensive… More >

Thomas Hanne^1,*, Mohammad Jahani Moghaddam²

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 4203-4236, 2025, DOI:10.32604/cmc.2025.068087 - 23 October 2025

Abstract Multi-Objective Evolutionary Algorithms (MOEAs) have significantly advanced the domain of Multi-Objective Optimization (MOO), facilitating solutions for complex problems with multiple conflicting objectives. This review explores the historical development of MOEAs, beginning with foundational concepts in multi-objective optimization, basic types of MOEAs, and the evolution of Pareto-based selection and niching methods. Further advancements, including decom-position-based approaches and hybrid algorithms, are discussed. Applications are analyzed in established domains such as engineering and economics, as well as in emerging fields like advanced analytics and machine learning. The significance of MOEAs in addressing real-world problems is emphasized, highlighting their More >

Yuqian Qi^*, Yanbo Che, Liangliang Liu, Jiayu Ni, Shangyuan Zhang

Energy Engineering, Vol.122, No.10, pp. 3999-4017, 2025, DOI:10.32604/ee.2025.068054 - 30 September 2025

Abstract The process of including renewable energy sources in power networks is moving quickly, so the need for innovative configuration solutions for grid-side ESS has grown. Among the new methods presented in this paper is GA-OCESE, which stands for Genetic Algorithm-based Optimization Configuration for Energy Storage in Electric Networks. This is one of the methods suggested in this study, which aims to enhance the sizing, positioning, and operational characteristics of structured ESS under dynamic grid conditions. Particularly, the aim is to maximize efficiency. A multiobjective genetic algorithm, the GA-OCESE framework, considers all these factors simultaneously. Besides… More >

Jian Li^1,*, Qing Zhang², Tong Yang², Yu’an Chen², Yongzhong Zhan³

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.3, pp. 3029-3051, 2025, DOI:10.32604/cmes.2025.068644 - 30 September 2025

Abstract In the deployment of wireless networks in two-dimensional outdoor campus spaces, aiming at the problem of efficient coverage of the monitoring area by limited number of access points (APs), this paper proposes a deployment method of multi-objective optimization with virtual force fusion bat algorithm (VFBA) using the classical four-node regular distribution as an entry point. The introduction of Lévy flight strategy for bat position updating helps to maintain the population diversity, reduce the premature maturity problem caused by population convergence, avoid the over aggregation of individuals in the local optimal region, and enhance the superiority… More >