Mengjiao Wei^1,*, Wenyu Liu²

CMC-Computers, Materials & Continua, Vol.83, No.2, pp. 2505-2523, 2025, DOI:10.32604/cmc.2025.060887 - 16 April 2025

Abstract In recent years, decomposition-based evolutionary algorithms have become popular algorithms for solving multi-objective problems in real-life scenarios. In these algorithms, the reference vectors of the Penalty-Based boundary intersection (PBI) are distributed parallelly while those based on the normal boundary intersection (NBI) are distributed radially in a conical shape in the objective space. To improve the problem-solving effectiveness of multi-objective optimization algorithms in engineering applications, this paper addresses the improvement of the Collaborative Decomposition (CoD) method, a multi-objective decomposition technique that integrates PBI and NBI, and combines it with the Elephant Clan Optimization Algorithm, introducing the… More >

Nour Elhouda Chalabi¹, Abdelouahab Attia², Abdulaziz S. Almazyad³, Ali Wagdy Mohamed^4,5, Frank Werner⁶, Pradeep Jangir⁷, Mohammad Shokouhifar^8,9,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.1, pp. 967-1008, 2025, DOI:10.32604/cmes.2025.062332 - 11 April 2025

Abstract Multi-objective optimization is critical for problem-solving in engineering, economics, and AI. This study introduces the Multi-Objective Chef-Based Optimization Algorithm (MOCBOA), an upgraded version of the Chef-Based Optimization Algorithm (CBOA) that addresses distinct objectives. Our approach is unique in systematically examining four dominance relations—Pareto, Epsilon, Cone-epsilon, and Strengthened dominance—to evaluate their influence on sustaining solution variety and driving convergence toward the Pareto front. Our comparison investigation, which was conducted on fifty test problems from the CEC 2021 benchmark and applied to areas such as chemical engineering, mechanical design, and power systems, reveals that the dominance approach More >

Sudipta Debnath¹, Zahir Uddin Ahmed², Muhammad Ikhlaq^3,4,*, Md. Tanvir Khan⁵, Avneet Kaur⁶, Kuljeet Singh Grewal¹

Frontiers in Heat and Mass Transfer, Vol.23, No.1, pp. 71-94, 2025, DOI:10.32604/fhmt.2024.059734 - 26 February 2025

Abstract Impinging jet arrays are extensively used in numerous industrial operations, including the cooling of electronics, turbine blades, and other high-heat flux systems because of their superior heat transfer capabilities. Optimizing the design and operating parameters of such systems is essential to enhance cooling efficiency and achieve uniform pressure distribution, which can lead to improved system performance and energy savings. This paper presents two multi-objective optimization methodologies for a turbulent air jet impingement cooling system. The governing equations are resolved employing the commercial computational fluid dynamics (CFD) software ANSYS Fluent v17. The study focuses on four… More > Graphic Abstract

Yuting Zhu^1,*, Wenyu Zhang^1,2, Hainan Wang¹, Junjie Hou¹, Haining Wang¹, Meng Wang¹

CMC-Computers, Materials & Continua, Vol.82, No.2, pp. 2177-2198, 2025, DOI:10.32604/cmc.2024.057441 - 17 February 2025

Abstract Addressing the complex issue of emergency resource distribution center site selection in uncertain environments, this study was conducted to comprehensively consider factors such as uncertainty parameters and the urgency of demand at disaster-affected sites. Firstly, urgency cost, economic cost, and transportation distance cost were identified as key objectives. The study applied fuzzy theory integration to construct a triangular fuzzy multi-objective site selection decision model. Next, the defuzzification theory transformed the fuzzy decision model into a precise one. Subsequently, an improved Chaotic Quantum Multi-Objective Harris Hawks Optimization (CQ-MOHHO) algorithm was proposed to solve the model. The… More >

Shumin Li¹, Qifang Luo^1,2,*, Yongquan Zhou^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1955-1994, 2025, DOI:10.32604/cmes.2025.059738 - 27 January 2025

Abstract Wireless sensor network deployment optimization is a classic NP-hard problem and a popular topic in academic research. However, the current research on wireless sensor network deployment problems uses overly simplistic models, and there is a significant gap between the research results and actual wireless sensor networks. Some scholars have now modeled data fusion networks to make them more suitable for practical applications. This paper will explore the deployment problem of a stochastic data fusion wireless sensor network (SDFWSN), a model that reflects the randomness of environmental monitoring and uses data fusion techniques widely used in… More >

Miloš Sedak^*, Maja Rosić, Božidar Rosić

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 2111-2145, 2025, DOI:10.32604/cmes.2025.059319 - 27 January 2025

Abstract This paper introduces a hybrid multi-objective optimization algorithm, designated HMODESFO, which amalgamates the exploratory prowess of Differential Evolution (DE) with the rapid convergence attributes of the Sailfish Optimization (SFO) algorithm. The primary objective is to address multi-objective optimization challenges within mechanical engineering, with a specific emphasis on planetary gearbox optimization. The algorithm is equipped with the ability to dynamically select the optimal mutation operator, contingent upon an adaptive normalized population spacing parameter. The efficacy of HMODESFO has been substantiated through rigorous validation against established industry benchmarks, including a suite of Zitzler-Deb-Thiele (ZDT) and Zeb-Thiele-Laumanns-Zitzler (DTLZ) More >

Ahmed Manguri^1,2,3,*, Hogr Hassan³, Najmadeen Saeed^3,4, Robert Jankowski¹

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 933-971, 2025, DOI:10.32604/cmes.2025.059249 - 27 January 2025

Abstract The optimization of civil engineering structures is critical for enhancing structural performance and material efficiency in engineering applications. Structural optimization approaches seek to determine the optimal design, by considering material performance, cost, and structural safety. The design approaches aim to reduce the built environment’s energy use and carbon emissions. This comprehensive review examines optimization techniques, including size, shape, topology, and multi-objective approaches, by integrating these methodologies. The trends and advancements that contribute to developing more efficient, cost-effective, and reliable structural designs were identified. The review also discusses emerging technologies, such as machine learning applications with More >

Li Ma¹, Cai Dai^1,*, Xingsi Xue², Cheng Peng³

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 997-1026, 2025, DOI:10.32604/cmc.2024.057168 - 03 January 2025

Abstract The multi-objective particle swarm optimization algorithm (MOPSO) is widely used to solve multi-objective optimization problems. In the article, a multi-objective particle swarm optimization algorithm based on decomposition and multi-selection strategy is proposed to improve the search efficiency. First, two update strategies based on decomposition are used to update the evolving population and external archive, respectively. Second, a multi-selection strategy is designed. The first strategy is for the subspace without a non-dominated solution. Among the neighbor particles, the particle with the smallest penalty-based boundary intersection value is selected as the global optimal solution and the particle… More >

Suliang Ma¹, Zeqing Meng¹, Mingxuan Chen^2,*, Yuan Jiang³

Energy Engineering, Vol.122, No.1, pp. 63-84, 2025, DOI:10.32604/ee.2024.057216 - 27 December 2024

Abstract In the independent electro-hydrogen system (IEHS) with hybrid energy storage (HESS), achieving optimal scheduling is crucial. Still, it presents a challenge due to the significant deviations in values of multiple optimization objective functions caused by their physical dimensions. These deviations seriously affect the scheduling process. A novel standardization fusion method has been established to address this issue by analyzing the variation process of each objective function’s values. The optimal scheduling results of IEHS with HESS indicate that the economy and overall energy loss can be improved 2–3 times under different optimization methods. The proposed method More > Graphic Abstract

Praveena Nuthakki¹, Pavan Kumar T.¹, Musaed Alhussein², Muhammad Shahid Anwar^3,*, Khursheed Aurangzeb², Leenendra Chowdary Gunnam⁴

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4743-4756, 2024, DOI:10.32604/cmc.2024.058266 - 19 December 2024

Abstract Cloud computing has emerged as a vital platform for processing resource-intensive workloads in smart manufacturing environments, enabling scalable and flexible access to remote data centers over the internet. In these environments, Virtual Machines (VMs) are employed to manage workloads, with their optimal placement on Physical Machines (PMs) being crucial for maximizing resource utilization. However, achieving high resource utilization in cloud data centers remains a challenge due to multiple conflicting objectives, particularly in scenarios involving inter-VM communication dependencies, which are common in smart manufacturing applications. This manuscript presents an AI-driven approach utilizing a modified Multi-Objective Particle More >