Article
Computer Science, Hardware & Architecture
Amjad Osmani, Jamshid Bagherzadeh Mohasefi, Farhad Soleimanian Gharehchopogh
Summary: The study introduces two famous metaheuristic methods, ABC optimization and ICA, and proposes two novel hybrid methods to improve optimization results. The study also explores feature selection and presents a solution. Evaluation results confirm the superior performance of the proposed methods.
Article
Computer Science, Software Engineering
Qiumei Pu, Chiquan Xu, Hui Wang, Lina Zhao
Summary: This paper proposes a novel clustering algorithm CEABC, enhanced by multiple operators and guided by a Gbest mechanism. The algorithm shows better accuracy and stability in solving clustering problems.
Article
Computer Science, Artificial Intelligence
Xu Chen, Hugo Tianfield, Wenli Du
Summary: This paper introduces a novel bee-foraging learning PSO (BFL-PSO) algorithm with three different search phases, showing very competitive performance in terms of solution accuracy.
APPLIED SOFT COMPUTING
(2021)
Article
Computer Science, Information Systems
Kai Li, Hui Wang, Wenjun Wang, Feng Wang, Zhihua Cui
Summary: This paper proposes an artificial bee colony algorithm based on a modified nearest neighbor sequence to enhance optimization capability. Experimental results show that the algorithm performs competitively on various benchmark problems and complex problems.
JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
(2022)
Article
Computer Science, Information Systems
Jiaxu Ning, Haitong Zhao, Chang Liu
Summary: An improved exhausted food source identification mechanism based on space partitioning is designed to address the issue of inefficient exploration and excessive searching resources allocation in existing ABC algorithms. The mechanism is applied to both the basic ABC algorithm and a recently improved version, showing better performance in almost all functions on the CEC2015 test suit compared to the original ABC algorithms.
Article
Computer Science, Theory & Methods
Xialin Zhang, Lingkun Lian, Fukang Zhu
Summary: The study improves the accuracy and automation of variogram fitting models through a hybrid algorithm, demonstrating stronger optimization ability and higher precision compared to traditional methods.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2021)
Article
Computer Science, Artificial Intelligence
Chenjun Tang, Wei Sun, Min Xue, Xing Zhang, Hongwei Tang, Wei Wu
Summary: This paper improves the defects and deficiencies of the recently proposed whale optimization algorithm (WOA) by proposing an artificial bee colony mixed whale optimization algorithm (ACWOA). The ACWOA algorithm integrates the artificial bee colony algorithm and chaotic mapping to avoid local optima and improve the quality of the initial solution. Nonlinear convergence factors and adaptive inertia weight coefficients are added to accelerate the convergence rate. Experimental results demonstrate the competitiveness of the ACWOA algorithm in terms of convergence speed and solution accuracy.
Article
Computer Science, Interdisciplinary Applications
Yue Xu, Xiuli Wang
Summary: This paper proposes a two-stage approach to solve the staff scheduling problem in call centers. The approach utilizes the artificial bee colony algorithm and integer programming to generate and optimize shift schedules. Experimental results demonstrate the effectiveness and efficiency of the proposed method in providing good solutions for large-scale problems. Additionally, guidance is provided on balancing employees' working preferences and labor costs with staff satisfaction.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Computer Science, Interdisciplinary Applications
Alireza Etminaniesfahani, Hanyu Gu, Amir Salehipour
Summary: The artificial bee colony (ABC) is a simple, flexible, and efficient metaheuristic optimization algorithm, but it suffers from slow convergence due to a lack of powerful local search capability. This paper proposes hybridizing ABC with the Fibonacci indicator algorithm (FIA) to achieve strong exploration and highly efficient exploitation capabilities, and it shows superior performance in various optimization functions.
JOURNAL OF COMPUTATIONAL SCIENCE
(2022)
Article
Computer Science, Information Systems
Serhat Kilicarslan, Emrah Donmez
Summary: This study introduces a novel approach combining adaptive particle swarm optimization and artificial bee colony algorithm to effectively classify microarray datasets for early diagnosis of cancer. The most defining features are selected through feature selection algorithms, and different classification algorithms are used for classification.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Multidisciplinary Sciences
Olatunji A. Akinola, Absalom E. Ezugwu, Olaide N. Oyelade, Jeffrey O. Agushaka
Summary: In this paper, a new hybrid method called BDMSAO is proposed, which combines the binary variants of the dwarf mongoose optimization algorithm (BDMO) and simulated annealing (SA) algorithm to solve mechanical engineering design problems. The hybrid algorithm, by utilizing different algorithms for global and local search, improves the effectiveness of feature selection problems and outperforms other methods in the study.
SCIENTIFIC REPORTS
(2022)
Article
Automation & Control Systems
Serap Ercan Comert, Harun Resit Yazgan
Summary: This paper introduces three multi-objective electric vehicle routing problems that consider different charging strategies and electric vehicle charger types while optimizing five conflicting objectives. A new hierarchical approach consisting of Hybrid Ant Colony Optimization (HACO) and Artificial Bee Colony Algorithm (ABCA) is developed to solve these problems. The proposed approach is examined on test-based instances and achieves the best new results in most cases.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Mathematics, Applied
Ya Zhang, Tong Li, Zhen Li, Yu-Mei Wu, Hong Miao
Summary: This paper proposes a BAS-ABC hybrid algorithm for parameter estimation in software defect prediction. The experimental results show that the hybrid algorithm outperforms the single algorithm in terms of accuracy, convergence, and stability, making it suitable for parameter estimation of the software reliability model.
Article
Computer Science, Artificial Intelligence
Yuan Zhao, Hong Liu, Kaizhou Gao
Summary: Simulation modeling is a crucial tool for studying crowd behavior and exploring emergency evacuation management methods. This paper proposes a new evacuation simulation method combining an improved artificial bee colony algorithm for dynamic path planning and SFM for simulating pedestrian movement, providing pedestrians with timely route selection. The new method shows superior performance in evacuating dense crowds efficiently in multiple scenarios and effectively shortening evacuation time.
APPLIED INTELLIGENCE
(2021)
Article
Computer Science, Artificial Intelligence
Hui Wang, Shuai Wang, Zichen Wei, Tao Zeng, Tingyu Ye
Summary: This paper proposes an improved many-objective artificial bee colony algorithm based on decomposition and dimension learning to solve many-objective optimization problems. The multi-objective problem is converted into several sub-problems by decomposition, and a new fitness function is defined. Elite solutions are selected based on their fitness values. The algorithm uses an elite set guided search strategy and dimension learning to improve convergence, and dynamically allocates computing resources in the scout bee stage. Experimental results show that this method outperforms seven other many-objective evolutionary algorithms.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Interdisciplinary Applications
Mohammadreza Koopialipoor, Bhatawdekar Ramesh Murlidhar, Ahmadreza Hedayat, Danial Jahed Armaghani, Behrouz Gordan, Edy Tonnizam Mohamad
ENGINEERING WITH COMPUTERS
(2020)
Article
Environmental Sciences
Mohammadreza Koopialipoor, Ebrahim Noroozi Ghaleini, Hossein Tootoonchi, Danial Jahed Armaghani, Mojtaba Haghighi, Ahmadreza Hedayat
ENVIRONMENTAL EARTH SCIENCES
(2019)
Article
Engineering, Geological
Deepanshu Shirole, Gabriel Walton, Ahmadreza Hedayat
INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES
(2020)
Article
Engineering, Geological
Deepanshu Shirole, Ahmadreza Hedayat, Ehsan Ghazanfari, Gabriel Walton
ROCK MECHANICS AND ROCK ENGINEERING
(2020)
Article
Chemistry, Multidisciplinary
Amir Mahdiyar, Danial Jahed Armaghani, Mohammadreza Koopialipoor, Ahmadreza Hedayat, Arham Abdullah, Khairulzan Yahya
APPLIED SCIENCES-BASEL
(2020)
Article
Geosciences, Multidisciplinary
M. A. Pirzada, H. Roshan, H. Sun, J. Oh, M. S. Andersen, A. Hedayat, M. Bahaaddini
JOURNAL OF STRUCTURAL GEOLOGY
(2020)
Article
Mechanics
Nan Zhang, Ahmadreza Hedayat, Shaoyang Han, Shuqi Ma, Hector Gelber Bolanos Sosa, Roberto Pedro Huamani Bernal, Nestor Tupa, Isaac Yanqui Morales, Reynaldo Sabino Canahua Loza
Summary: This study aimed to improve the mechanical and fracture properties of mine tailings-based geopolymer by using class F fly ash (FA) as an amorphous supplements source. The results showed that the addition of FA had an influence on the fracture behavior of the geopolymer, and this influence was related to the microscopic characteristics of the material.
ENGINEERING FRACTURE MECHANICS
(2022)
Article
Polymer Science
Yibran Perera-Mercado, Ahmadreza Hedayat, Lori Tunstall, Cara Clements, Julia Hylton, Linda Figueroa, Nan Zhang, Hector Gelber Bolanos Sosa, Nestor Tupa, Isaac Yanqui Morales, Reynaldo Sabino Canahua Loza
Summary: Beneficiation of industrial wastes, such as mine tailings (MTs), through development of alternative eco-friendly geopolymer binders for construction composites offers a twofold environmental benefit, as it reduces the demand for cement and it increases the sustainability of industrial processes by creating a value-added product from an industrial byproduct. The study found that the combination of Class C Fly Ash (FAc) with low-reactive gold MTs improved the physicochemical stability of the geopolymerized samples, resulting in a significant increase in compressive strength. The presence of FAc also improved the reactivity of the MTs, increasing the geopolymer production.
Article
Engineering, Geological
Ahmadreza Hedayat, Pierpaolo Oreste, Giovanni Spagnoli
Summary: The properties of rock mass are influenced by excavation techniques and changes in stress levels caused by rock excavation. The impact of blasting is significant near tunnel periphery due to wave energy and stress redistribution, but damage severity decreases with radial distance. It is important to consider the damaged zone when analyzing stresses and deformations around a tunnel.
GEOMECHANICS AND GEOENGINEERING-AN INTERNATIONAL JOURNAL
(2021)
Proceedings Paper
Engineering, Civil
Sana Zafar, Ahmadreza Hedayat, Omid Moradian
GEOTECHNICAL EARTHQUAKE ENGINEERING AND SPECIAL TOPICS (GEO-CONGRESS 2020)
(2020)
Proceedings Paper
Construction & Building Technology
Ketan Arora, Marte Gutierrez, Ahmadreza Hedayat
ENGINEERING, MONITORING, AND MANAGEMENT OF GEOTECHNICAL INFRASTRUCTURE (GEO-CONGRESS 2020 )
(2020)
Proceedings Paper
Computer Science, Interdisciplinary Applications
Amin Gheibi, Lucy Davis, Ahmadreza Hedayat
MODELING, GEOMATERIALS, AND SITE CHARACTERIZATION (GEO-CONGRESS 2020)
(2020)
Article
Engineering, Geological
Pierpaolo Oreste, Giovanni Spagnoli, Cesar Alejandro Luna Ramos, Ahmadreza Hedayat
GEOTECHNICAL AND GEOLOGICAL ENGINEERING
(2019)
Article
Engineering, Civil
Hadi Haeri, V. Sarfarazi, Zheming Zhu, N. Nohekhan Hokmabadi, M. R. Moshrefifar, A. Hedayat
STRUCTURAL ENGINEERING AND MECHANICS
(2019)