Article
Computer Science, Artificial Intelligence
Hebatullah Khattab, Basel A. Mahafzah, Ahmad Sharieh
Summary: This paper proposes a new approach for solving the MVCP problem by hybridizing an improved CRO algorithm and the BFS algorithm. Experimental results show that this approach outperforms several other metaheuristic algorithms in terms of performance metrics.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Zhe Shu, Zhiwei Ye, Xinlu Zong, Shiqin Liu, Daode Zhang, Chunzhi Wang, Mingwei Wang
Summary: The paper introduces a novel hybrid rice optimization algorithm inspired by the breeding process of Chinese three-line hybrid rice for solving the 0-1 knapsack problem. It combines dynamic step size adjustment and binary ant colony optimization algorithm, and proposes parallel and serial models to enhance search efficiency and convergence speed. The experimental results demonstrate the superiority of the parallel and serial models in solving 0-1 knapsack problems of different scales and correlations.
APPLIED INTELLIGENCE
(2022)
Article
Computer Science, Artificial Intelligence
Yunpeng Ma, Xinxin Zhang, Jiancai Song, Lei Chen
Summary: The modified teaching-learning-based optimization algorithm (MTLBO) reduces the NOx emissions concentration of a circulation fluidized bed boiler through a new population group mechanism, demonstrating better solution quality and faster convergence speed compared to other optimization algorithms.
KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Interdisciplinary Applications
Qinglei Zhai, Yichao He, Gaige Wang, Xiang Hao
Summary: Hardware/software partitioning is a significant problem in hardware-software co-design, and it is an NP-hard problem. In this study, a new greedy algorithm is proposed to solve the HW/SW problem effectively, and a general algorithm framework based on discrete evolutionary algorithm is introduced. By comparing the calculation results of various algorithms, it is confirmed that group theory-based optimization algorithm and binary particle swarm optimization are more suitable for solving large-scale HW/SW instances.
ADVANCES IN ENGINEERING SOFTWARE
(2021)
Article
Computer Science, Artificial Intelligence
Yassine Saji, Mohammed Barkatou
Summary: The bat algorithm, a swarm-intelligence-based metaheuristic introduced in 2010, continues to be widely used due to its simplicity and applicability. However, it may face the challenge of getting trapped in local optima when dealing with large complex problems.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Engineering, Multidisciplinary
Shutong Xie, Zongbao He, Xingwang Huang
Summary: The multi-pass turning operation is a commonly used machining method in the manufacturing field, aiming to minimize the unit production cost. This paper proposes a Gaussian quantum-behaved bat algorithm (GQBA) to solve this problem. The algorithm incorporates the current optimal positions of quantum bats and the global best position to facilitate population diversification, and uses a Gaussian distribution to update the positions for more accurate search. Experimental results show that GQBA has better search capability and outperforms other algorithms in terms of cost reduction.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2023)
Article
Computer Science, Artificial Intelligence
Masoud Dashtdar, Mohit Bajaj, Seyed Mohammad Sadegh Hosseinimoghadam, Hamed Mershekaer
Summary: This paper discusses the issue of fault location in distribution networks, proposing an optimization model based on smart meter data and power flow method to locate faults. The results show that the proposed method performs well under different fault conditions.
Article
Engineering, Electrical & Electronic
Masoud Dashtdar, Arif Hussain, Hassan Z. Al Garni, Abdullahi Abubakar Mas'ud, Waseem Haider, Kareem M. AboRas, Hossam Kotb
Summary: In this research, distribution network fault location is defined as an optimization problem, and the network fault location is determined by solving it. Two new objective functions are designed to identify the faulty section and fault location based on calculating the voltage difference between the two ends of the grid lines. The advantages of the proposed algorithm include simplicity, step-by-step implementation, efficiency in conditions of different branch specifications, application for various types of faults, and its optimal accuracy compared to other methods.
Article
Chemistry, Multidisciplinary
Jianguo Zheng, Yilin Wang
Summary: A hybrid bat optimization algorithm is proposed in this paper to solve a three-stage distributed assembly permutation flowshop scheduling problem, with the aim of minimizing makespan. By classifying populations, utilizing a selection mechanism, and implementing learning strategies to aid the population in jumping out of local optimal frontiers, the algorithm effectively addresses the trade-offs between convergence, diversity, exploration, and mining capacity. The simulation results show that the proposed algorithm outperforms other metaheuristic algorithms in solving the DAPFSP.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Artificial Intelligence
Indadul Khan, Prasanta Dutta, Manas Kumar Maiti, Krishnendu Basuli
Summary: In this study, the Bat algorithm (BA) is modified with K-opt operation and a newly proposed perturbation approach to solve the covering salesman problem (CSP). A new perturbation approach called K-bit exchange operation is also proposed. The modified BA embedded with K-bit exchange and K-opt operation (MBAKEKO) outperforms other algorithms in finding the minimum cost tour for the CSP.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Ping Guo, Yang Zhang
Summary: The ISSATA algorithm, which incorporates new initialization, variable selection, and neighbor priority strategies, improves the efficiency and accuracy of solving the 3-satisfiability problem.
APPLIED INTELLIGENCE
(2022)
Article
Computer Science, Information Systems
Waqas Haider Bangyal, Abdul Hameed, Jamil Ahmad, Kashif Nisar, Muhammad Reazul Haque, Ag. Asri Ag. Ibrahim, Joel J. P. C. Rodrigues, M. Adil Khan, Danda B. Rawat, Richard Etengu
Summary: The Bat algorithm (BA) is a well-known meta-heuristic algorithm used for solving optimization problems. This study proposes an improved variation of BA, called the Modern Computerized Bat Algorithm (MCBA), which applies torus walk to enhance local search capability. Experimental results demonstrate that MCBA outperforms standard PSO and BA, and the MCBA-NN algorithm shows promising performance for training artificial neural networks.
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
Article
Mathematics, Applied
Mengjian Zhang, Deguang Wang, Ming Yang, Wei Tan, Jing Yang
Summary: This study proposes a novel hybrid algorithm (HPSBA) for solving the Wireless Sensor Network (WSN) coverage optimization problem by combining the strengths of particle swarm optimization (PSO) and butterfly optimization algorithm (BOA). Experimental results demonstrate that HPSBA achieves higher coverage rate and extends the network survival time.
Article
Computer Science, Artificial Intelligence
Sepideh Mohammadi, Behrooz Alizadeh, Fahimeh Baroughi, Esmaeil Afrashteh
Summary: This paper discusses an extensive variant of the inverse p-facility maxian location problem on networks and proposes a novel modified algorithm to solve the problem, demonstrating its effectiveness through computational tests.
Article
Computer Science, Interdisciplinary Applications
K. Gulnaz Bulbul, Refail Kasimbeyli
Summary: This paper studies a new version of the aircraft maintenance routing problem, formulating it as an asymmetric traveling salesman problem with fleet size and maintenance violation constraints. A hybrid solution method combining a modified subgradient algorithm and ant colony optimization metaheuristic is developed and demonstrated to outperform conventional methods.
COMPUTERS & OPERATIONS RESEARCH
(2021)
