Ibrahim T. Teke^1,2, Ahmet H. Ertas^2,*

CMC-Computers, Materials & Continua, Vol.84, No.1, pp. 243-264, 2025, DOI:10.32604/cmc.2025.066086 - 09 June 2025

Abstract This study presents a novel hybrid topology optimization and mold design framework that integrates process fitting, runner system optimization, and structural analysis to significantly enhance the performance of injection-molded parts. At its core, the framework employs a greedy algorithm that generates runner systems based on adjacency and shortest path principles, leading to improvements in both mechanical strength and material efficiency. The design optimization is validated through a series of rigorous experimental tests, including three-point bending and torsion tests performed on key-socket frames, ensuring that the optimized designs meet practical performance requirements. A critical innovation of… More >

Pravinkumar Bhujangrao Landge¹, Yashpal Singh¹, Hitesh Mohapatra², Seyyed Ahmad Edalatpanah^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.143, No.2, pp. 1661-1688, 2025, DOI:10.32604/cmes.2025.065599 - 30 May 2025

Abstract Internet of things networks often suffer from early node failures and short lifespan due to energy limits. Traditional routing methods are not enough. This work proposes a new hybrid algorithm called ACOGA. It combines Ant Colony Optimization (ACO) and the Greedy Algorithm (GA). ACO finds smart paths while Greedy makes quick decisions. This improves energy use and performance. ACOGA outperforms Hybrid Energy-Efficient (HEE) and Adaptive Lossless Data Compression (ALDC) algorithms. After 500 rounds, only 5% of ACOGA’s nodes are dead, compared to 15% for HEE and 20% for ALDC. The network using ACOGA runs for More >

Wenpeng Li¹, Zhenghe Liu¹, Yujing Ma¹, Zhuxuan Meng^2,*, Ji Ma³, Weisong Liu², Vinh Phu Nguyen⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 1515-1543, 2025, DOI:10.32604/cmes.2025.059235 - 27 January 2025

Abstract This paper presents a framework for constructing surrogate models for sensitivity analysis of structural dynamics behavior. Physical models involving deformation, such as collisions, vibrations, and penetration, are developed using the material point method. To reduce the computational cost of Monte Carlo simulations, response surface models are created as surrogate models for the material point system to approximate its dynamic behavior. An adaptive randomized greedy algorithm is employed to construct a sparse polynomial chaos expansion model with a fixed order, effectively balancing the accuracy and computational efficiency of the surrogate model. Based on the sparse polynomial More >

Binhui Wang, Hongfeng Wang^*

CMC-Computers, Materials & Continua, Vol.82, No.1, pp. 371-388, 2025, DOI:10.32604/cmc.2024.058885 - 03 January 2025

Abstract The distributed permutation flow shop scheduling problem (DPFSP) has received increasing attention in recent years. The iterated greedy algorithm (IGA) serves as a powerful optimizer for addressing such a problem because of its straightforward, single-solution evolution framework. However, a potential draw-back of IGA is the lack of utilization of historical information, which could lead to an imbalance between exploration and exploitation, especially in large-scale DPFSPs. As a consequence, this paper develops an IGA with memory and learning mechanisms (MLIGA) to efficiently solve the DPFSP targeted at the mini-mal makespan. In MLIGA, we incorporate a memory… More >

Xiaoqing Wang¹, Peng Duan^1,*, Leilei Meng^1,*, Kaidong Yang²

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 931-947, 2024, DOI:10.32604/cmc.2024.050612 - 18 July 2024

Abstract Effective path planning is crucial for mobile robots to quickly reach rescue destination and complete rescue tasks in a post-disaster scenario. In this study, we investigated the post-disaster rescue path planning problem and modeled this problem as a variant of the travel salesman problem (TSP) with life-strength constraints. To address this problem, we proposed an improved iterated greedy (IIG) algorithm. First, a push-forward insertion heuristic (PFIH) strategy was employed to generate a high-quality initial solution. Second, a greedy-based insertion strategy was designed and used in the destruction-construction stage to increase the algorithm’s exploration ability. Furthermore,… More >

Linlin Yuan^1,2, Tiantian Zhang^1,3, Yuling Chen^1,*, Yuxiang Yang¹, Huang Li¹

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 1561-1579, 2024, DOI:10.32604/cmc.2023.046907 - 25 April 2024

Abstract The development of technologies such as big data and blockchain has brought convenience to life, but at the same time, privacy and security issues are becoming more and more prominent. The K-anonymity algorithm is an effective and low computational complexity privacy-preserving algorithm that can safeguard users’ privacy by anonymizing big data. However, the algorithm currently suffers from the problem of focusing only on improving user privacy while ignoring data availability. In addition, ignoring the impact of quasi-identified attributes on sensitive attributes causes the usability of the processed data on statistical analysis to be reduced. Based… More >

Deshun Li¹, Zhenchen Wang², Yucong Wei², Jiangyuan Yao^1,*, Yuyin Tan², Qiuling Yang¹, Zhengxia Wang¹, Xingcan Cao³

CMC-Computers, Materials & Continua, Vol.76, No.1, pp. 561-572, 2023, DOI:10.32604/cmc.2023.033332 - 08 June 2023

Abstract Delay and stability are two key factors that affect the performance of multicast data transmission in a network. However, current algorithms of tree generation hardly meet the requirements of low delay and high stability simultaneously. Given a general network, the generation algorithm of a multicast tree with minimum delay and maximum stability is an NP-hard problem, without a precise and efficient algorithm. To address these challenges, this paper studies the generation of low-delay and high-stability multicast trees under the model of spanning tree based on stability probability, degree-constrained, edge-weighted for multicast (T-SDE). A class of algorithms… More >

Rakhshan Zulfiqar^1,2, Tariq Javed¹, Zain Anwar Ali^2,*, Eman H. Alkhammash³, Myriam Hadjouni⁴

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 985-1000, 2023, DOI:10.32604/iasc.2023.037248 - 29 April 2023

Abstract The deployment of sensor nodes is an important aspect in mobile wireless sensor networks for increasing network performance. The longevity of the networks is mostly determined by the proportion of energy consumed and the sensor nodes’ access network. The optimal or ideal positioning of sensors improves the portable sensor networks effectiveness. Coverage and energy usage are mostly determined by successful sensor placement strategies. Nature-inspired algorithms are the most effective solution for short sensor lifetime. The primary objective of work is to conduct a comparative analysis of nature-inspired optimization for wireless sensor networks (WSNs’) maximum network More >

Hissah A. Ben Zayed, Mashael S. Maashi^*

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 307-318, 2021, DOI:10.32604/iasc.2021.017239 - 12 May 2021

Abstract Software testing is a fundamental step in the software development lifecycle. Its purpose is to evaluate the quality of software applications. Regression testing is an important testing methodology in software testing. The purpose of regression testing is to validate the software after each change of its code. This involves adding new test cases to the test suite and running the test suite as the software changes, making the test suite larger. The cost and time of the project are affected by the test suite size. The challenge is to run regression testing with a smaller… More >

Yizhi Liu^1,2, Rutian Qing^1,2,*, Liangran Wu^1,2, Min Liu^1,2, Zhuhua Liao^1,2, Yijiang Zhao^1,2

Journal on Artificial Intelligence, Vol.3, No.1, pp. 33-43, 2021, DOI:10.32604/jai.2021.016565 - 02 April 2021

Abstract In the large-scale logistics distribution of single logistic center, the method based on traditional genetic algorithm is slow in evolution and easy to fall into the local optimal solution. Addressing at this issue, we propose a novel approach of exploring hybrid genetic algorithm based large-scale logistic distribution for BBG supermarket. We integrate greedy algorithm and hillclimbing algorithm into genetic algorithm. Greedy algorithm is applied to initialize the population, and then hill-climbing algorithm is used to optimize individuals in each generation after selection, crossover and mutation. Our approach is evaluated on the dataset of BBG Supermarket More >