Article
Operations Research & Management Science
Chunfeng Liu, Xiao Yang, Jufeng Wang
Summary: In the era of mass customization, designing optimal products has become crucial for companies to maintain competitiveness. It is essential for companies to consider customer preferences, product quality, cost control, and delivery time in the product design and production process to avoid unreasonable product configurations and high production costs. The proposed Discrete Imperialist Competitive Algorithm (DICA) shows significant improvement in solution quality compared to genetic algorithm (GA) and simulated annealing (SA) in solving the integrated product line design and production problem.
RAIRO-OPERATIONS RESEARCH
(2021)
Article
Computer Science, Artificial Intelligence
Xin-rui Tao, Jun-qing Li, Ti-hao Huang, Peng Duan
Summary: The research on resource-constrained hybrid flowshop problem led to the proposal of a discrete imperialist competitive algorithm (DICA) to minimize makespan and energy consumption. The algorithm represents solutions using two-dimensional vectors, with one for scheduling sequence and the other for machine assignment, and incorporates a decoding method considering resource allocation. By combining DICA with simulated annealing algorithm (SA), the proposed approach showed high efficiency in solving the RCHFS problem.
COMPLEX & INTELLIGENT SYSTEMS
(2021)
Article
Energy & Fuels
Majid Khanali, Asadollah Akram, Javad Behzadi, Fatemeh Mostashari-Rad, Zahra Saber, Kwok-wing Chau, Ashkan Nabavi-Pelesaraei
Summary: The study focuses on the energy flow and environmental emissions of walnut orchards in Alborz province of Iran, aiming to optimize them through a multi-objective imperialist competitive algorithm. Results show energy inefficiency in walnut production, with gasoline being the dominant energy consumer. Environmental findings indicate on-orchard emissions and gasoline as the main hotspots.
Article
Geochemistry & Geophysics
Amir Joolaei, Alireza Arab-Amiri, Ali Nejati
Summary: Traditionally, local deterministic optimization techniques have been used for nonlinear gravity inversion problems, but recently global optimization methods such as a hybrid of ICA and FA algorithm have shown promising results. This hybrid method improves exploratory capability and convergence rate, making it a potential alternative to local optimization techniques in highly nonlinear geophysical problems.
Article
Computer Science, Interdisciplinary Applications
A. Kaveh, P. Rahmani, A. Dadras Eslamlou
Summary: This paper introduces a new hybrid algorithm ICHHO, combining HHO and ICA, which successfully improves the search strategy and demonstrates competitive performance through comparisons with other techniques and problems.
ENGINEERING WITH COMPUTERS
(2022)
Article
Construction & Building Technology
Jianyang Cai, Haidong Yang, Tiancheng Lai, Kangkang Xu
Summary: A new optimization algorithm based on an improved imperialist competitive algorithm (ICA-DE) is proposed to reduce the energy consumption of a multi-chiller system. The idea of differential mutation proposed by differential evolution (DE) was applied to create more new locations for colonies and increase population diversity in the assimilation process of ICA. The ICA-DE method was used to distribute the partial load rate (PLR) of chillers and achieved good results in reducing energy consumption.
ENERGY AND BUILDINGS
(2023)
Article
Mathematics
Marius Gavrilescu, Sabina-Adriana Floria, Florin Leon, Silvia Curteanu
Summary: This paper introduces a novel neural network optimization method that combines improved evolutionary competitive algorithm and gradient-based backpropagation. By incorporating backpropagation and self-adaptive hyperparameter adjustment strategy, this method generates regression models that are better correlated with the desired outputs and provides more accurate predictions.
Article
Computer Science, Artificial Intelligence
Xia Li, Junhan Chen, Lingfang Sun, Jing Li
Summary: Intelligent optimization algorithms play an important role in solving global optimization problems. The imperialist competitive algorithm (ICA), a nature-inspired meta-heuristic algorithm, tends to fall into local optima. To address this issue, an improved ICA algorithm is proposed, which incorporates the theory of spiral rising to expand search space and enhance global search ability.
PEERJ COMPUTER SCIENCE
(2022)
Article
Telecommunications
E. Shafiee, M. R. Mosavi, M. Moazedi
Summary: This paper presents an intelligent dynamic algorithm-based GPS spoofing attack detection method that detects spoofing behavior by distinguishing correlation peaks of authentic and counterfeit signals, and validations show that it can successfully detect spoofing attacks in 99.7% of cases.
WIRELESS PERSONAL COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Egon Henrique Salerno Galembeck, Salvador Pinillos Gimenez, Rodrigo Alves de Lima Moreto
Summary: The design and optimization of analog CMOS ICs are complex and dependent on designers' experience, with long design cycle times. This study presents the first use of a custom imperialist competitive algorithm (ICA) to reduce the design cycle times of analog CMOS ICs. The results show that using an ICA-customized evolutionary algorithm can reduce the design cycle times by up to 83% compared to using a GA-customized evolutionary algorithm.
Article
Computer Science, Information Systems
Keyvan Golalipour
Summary: With the widespread use of smartphones and mobile internet, there has been explosive growth in the sharing of images on social media networks. This paper proposes a hybrid model that combines a novel permutation technique with a diffusion method based on a chaotic function. The results show that the proposed method has excellent resistance against brute force and statistical attacks.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Biology
Mehdi Ayar, Ayaz Isazadeh, Farhad Soleimanian Gharehchopogh, MirHojjat Seyedi
Summary: This study proposes a multi-objective, non-dominated, imperialist competitive algorithm (NSICA) for optimal feature selection. The NSICA is a modified version of the original Imperialist Competitive Algorithm (ICA) that solves optimization problems through competition between colonies and imperialists. By modifying the operations and using a non-dominated sorting approach, this study addresses challenges such as discretization and elitism. The proposed algorithm is application-independent and can be customized for any feature selection problem. Evaluation results show the efficiency of NSICA compared to other state-of-the-art algorithms, using it as a feature selection system for diagnosing cardiac arrhythmias.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Computer Science, Artificial Intelligence
Babak Rezaei, Frederico Gadelha Guimaraes, Rasul Enayatifar, Pauline C. Haddow
Summary: This article introduces a hybrid metaheuristic algorithm, ICAHGS, for solving the Capacitated Vehicle Routing Problem (CVRP). The algorithm combines the refined Imperialist Competitive Algorithm (ICA) and the Hybrid Genetic Search (HGS-CVRP) algorithm, with a multi-step restart mechanism for intensification improvement. The proposed method allows for parallel processing, resulting in increased computational efficiency. Comparative experiments demonstrate the competitive performance of the proposed algorithm.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Mohammad Reza Afshar, Masoud Zavari
Summary: The selection of subcontractors is crucial for the success of a project as it can significantly impact the project's outcomes. Choosing the wrong subcontractor can result in delays and cost overruns, highlighting the importance of selecting the best subcontractor.
Article
Operations Research & Management Science
F. Shakouhi, R. Tavakkoli-Moghaddam, A. Baboli, A. Bozorgi-Amiri
Summary: This paper addresses competition problems in two pharmaceutical supply chains by analyzing the impact of marketing strategies on demand and offering Nash and Stackelberg games under the product life cycle. The results show that the average total profit of the supply chains at Nash equilibrium is 6.5 times that of Stackelberg, with the second supply chain experiencing significantly higher profits.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Engineering, Multidisciplinary
Salman Nazari-Shirkouhi, Abbas Keramati, Kamran Rezaie
TEHNICKI VJESNIK-TECHNICAL GAZETTE
(2015)
Article
Green & Sustainable Science & Technology
Saeed Mousakhani, Salman Nazari-Shirkouhi, Ali Bozorgi-Amiri
JOURNAL OF CLEANER PRODUCTION
(2017)
Article
Computer Science, Artificial Intelligence
Salman Nazari-Shirkouhi, Sina Miri-Nargesi, Ayyub Ansarinejad
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2017)
Article
Computer Science, Cybernetics
Mohammad Reza Taghizadeh Yazdi, Mohammad Mahdi Mozaffari, Salman Nazari-Shirkouhi, Seyed Mohammad Asadzadeh
CYBERNETICS AND SYSTEMS
(2018)
Article
Engineering, Multidisciplinary
Kamran Rezaie, Sara Saeidi Ramiyani, Salman Nazari-Shirkouhi, Ali Badizadeh
APPLIED MATHEMATICAL MODELLING
(2014)
Article
Computer Science, Artificial Intelligence
Homa Samadi, Salman Nazari-Shirkouhi, Abbas Keramati
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2014)
Article
Computer Science, Cybernetics
Mohammad Mahdi Mozaffari, Mohammadreza Taghizadeh-Yazdi, Salman Nazari-Shirkouhi, Seyed Mohammad Asadzadeh
Summary: The paper introduces a new data-driven method to measure the impact of road safety culture on road fatalities, using data envelopment analysis (DEA) instead of questionnaire surveys. DEA results can differentiate provinces based on cultural factors influencing fatality rates and show improvements in road safety culture in Iran over a two-year period.
CYBERNETICS AND SYSTEMS
(2021)
Article
Environmental Sciences
Nima Alipour, Salman Nazari-Shirkouhi, Mohamad Sadegh Sangari, Hadi Rezaei Vandchali
Summary: This study explores the impact of lean, agile, resilient, and green (LARG) concepts on human resource management, finding that LARG HRM significantly influences organizational performance and indirectly affects it through promoting organizational innovation. Among the four paradigms, enhancing employee capabilities, focusing on employee participation in decision-making, improving employee adaptability, and ensuring employee understanding of environmental policies are the most effective factors.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Salman Nazari-Shirkouhi, Mahdokht Tavakoli, Kannan Govindan, Saeed Mousakhani
Summary: This paper proposes a new integrated approach for resilient supplier selection in the pharmaceutical industry, considering both traditional and resilience criteria. The approach utilizes the Z-DEA model and artificial neural network, and expert opinions based on Z-numbers. A real case study is used to demonstrate the applicability of the approach, and performance analysis confirms its features and capabilities.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Health Policy & Services
Madjid Tavana, Salman Nazari-Shirkouhi, Hamidreza Farzaneh Kholghabad
Summary: The study proposes an integrated quality and resilience engineering framework for evaluating medical equipment suppliers' performance. It shows that factors such as flexibility, conformance to standards, cost, quality certifications, and delivery time significantly affect the suppliers' performance. This integrated framework is demonstrated to be more efficient and informative than standalone quality engineering or resiliency engineering approaches.
HEALTH CARE MANAGEMENT SCIENCE
(2021)
Article
Business
Salman Nazari-Shirkouhi, Saeed Mousakhani, Mahdokht Tavakoli, Mohammad Reza Dalvand, Jonas Saparauskas, Jurgita Antucheviciene
JOURNAL OF BUSINESS ECONOMICS AND MANAGEMENT
(2020)
Proceedings Paper
Engineering, Industrial
Nima Alipour, Mohamad Sadegh Sangari, Salman Nazari-Shirkouhi
PROCEEDINGS OF 2019 15TH IRAN INTERNATIONAL INDUSTRIAL ENGINEERING CONFERENCE (IIIEC)
(2019)
Article
Management
Hamidreza Farzaneh Kholghabad, Negin Alisoltani, Salman Nazari-Shirkouhi, Mohammadali Azadeh, Saeed Moosakhani
IRANIAN JOURNAL OF MANAGEMENT STUDIES
(2019)
Article
Engineering, Multidisciplinary
Salman Nazari-Shirkouhi, Abbas Keramati
APPLIED MATHEMATICAL MODELLING
(2017)
Article
Engineering, Multidisciplinary
Hanialhossein Abolfazli, Seyed Masoud Asadzadeh, Salman Nazari-Shirkouhi, Seyed Mohammad Asadzadeh, Kamran Rezaie
ACTA POLYTECHNICA HUNGARICA
(2014)
Review
Computer Science, Artificial Intelligence
Wei Gao, Shuangshuang Ge
Summary: This study provides a comprehensive review of slope stability research based on artificial intelligence methods, focusing on slope stability computation and evaluation. The review covers studies using quasi-physical intelligence methods, simulated evolutionary methods, swarm intelligence methods, hybrid intelligence methods, artificial neural network methods, vector machine methods, and other intelligence methods. The merits, demerits, and state-of-the-art research advancement of these studies are analyzed, and possible research directions for slope stability investigation based on artificial intelligence methods are suggested.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Khuong Le Nguyen, Hoa Thi Trinh, Saeed Banihashemi, Thong M. Pham
Summary: This study investigated the influence of input parameters on the shear strength of RC squat walls and found that ensemble learning models, particularly XGBoost, can effectively predict the shear strength. The axial load had a greater influence than reinforcement ratio, and longitudinal reinforcement had a more significant impact compared to horizontal and vertical reinforcement. The performance of XGBoost model outperforms traditional design models and reducing input features still yields reliable predictions.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Bo Hu, Huiyan Zhang, Xiaoyi Wang, Li Wang, Jiping Xu, Qian Sun, Zhiyao Zhao, Lei Zhang
Summary: A deep hierarchical echo state network (DHESN) is proposed to address the limitations of shallow coupled structures. By using transfer entropy, candidate variables with strong causal relationships are selected and a hierarchical reservoir structure is established to improve prediction accuracy. Simulation results demonstrate that DHESN performs well in predicting algal bloom.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Limin Wang, Lingling Li, Qilong Li, Kuo Li
Summary: This paper discusses the urgency of learning complex multivariate probability distributions due to the increase in data variability and quantity. It introduces a highly scalable classifier called TAN, which utilizes maximum weighted spanning tree (MWST) for graphical modeling. The paper theoretically proves the feasibility of extending one-dependence MWST to model high-dependence relationships and proposes a heuristic search strategy to improve the fitness of the extended topology to data. Experimental results demonstrate that this algorithm achieves a good bias-variance tradeoff and competitive classification performance compared to other high-dependence or ensemble learning algorithms.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Zhejing Hu, Gong Chen, Yan Liu, Xiao Ma, Nianhong Guan, Xiaoying Wang
Summary: Anxiety is a prevalent issue and music therapy has been found effective in reducing anxiety. To meet the diverse needs of individuals, a novel model called the spatio-temporal therapeutic music transfer model (StTMTM) is proposed.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Nur Ezlin Zamri, Mohd. Asyraf Mansor, Mohd Shareduwan Mohd Kasihmuddin, Siti Syatirah Sidik, Alyaa Alway, Nurul Atiqah Romli, Yueling Guo, Siti Zulaikha Mohd Jamaludin
Summary: In this study, a hybrid logic mining model was proposed by combining the logic mining approach with the Modified Niche Genetic Algorithm. This model improves the generalizability and storage capacity of the retrieved induced logic. Various modifications were made to address other issues. Experimental results demonstrate that the proposed model outperforms baseline methods in terms of accuracy, precision, specificity, and correlation coefficient.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
David Jacob Kedziora, Tien-Dung Nguyen, Katarzyna Musial, Bogdan Gabrys
Summary: The paper addresses the problem of efficiently optimizing machine learning solutions by reducing the configuration space of ML pipelines and leveraging historical performance. The experiments conducted show that opportunistic/systematic meta-knowledge can improve ML outcomes, and configuration-space culling is optimal when balanced. The utility and impact of meta-knowledge depend on various factors and are crucial for generating informative meta-knowledge bases.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
G. Sophia Jasmine, Rajasekaran Stanislaus, N. Manoj Kumar, Thangamuthu Logeswaran
Summary: In the context of a rapidly expanding electric vehicle market, this research investigates the ideal locations for EV charging stations and capacitors in power grids to enhance voltage stability and reduce power losses. A hybrid approach combining the Fire Hawk Optimizer and Spiking Neural Network is proposed, which shows promising results in improving system performance. The optimization approach has the potential to enhance the stability and efficiency of electric grids.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Zhijiang Wu, Guofeng Ma
Summary: This study proposes a natural language processing-based framework for requirement retrieval and document association, which can help to mine and retrieve documents related to project managers' requirements. The framework analyzes the ontology relevance and emotional preference of requirements. The results show that the framework performs well in terms of iterations and threshold, and there is a significant matching between the retrieved documents and the requirements, which has significant managerial implications for construction safety management.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Yung-Kuan Chan, Chuen-Horng Lin, Yuan-Rong Ben, Ching-Lin Wang, Shu-Chun Yang, Meng-Hsiun Tsai, Shyr-Shen Yu
Summary: This study proposes a novel method for dog identification using nose-print recognition, which can be applied to controlling stray dogs, locating lost pets, and pet insurance verification. The method achieves high recognition accuracy through two-stage segmentation and feature extraction using a genetic algorithm.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Shaohua Song, Elena Tappia, Guang Song, Xianliang Shi, T. C. E. Cheng
Summary: This study aims to optimize supplier selection and demand allocation decisions for omni-channel retailers in order to achieve supply chain resilience. It proposes a two-phase approach that takes into account various factors such as supplier evaluation and demand allocation.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Jinyan Hu, Yanping Jiang
Summary: This paper examines the allocation problem of shared parking spaces considering parking unpunctuality and no-shows. It proposes an effective approach using sample average approximation (SAA) combined with an accelerating Benders decomposition (ABD) algorithm to solve the problem. The numerical experiments demonstrate the significance of supply-demand balance for the operation and user satisfaction of the shared parking system.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Review
Computer Science, Artificial Intelligence
Soroor Motie, Bijan Raahemi
Summary: Financial fraud is a persistent problem in the finance industry, but Graph Neural Networks (GNNs) have emerged as a powerful tool for detecting fraudulent activities. This systematic review provides a comprehensive overview of the current state-of-the-art technologies in using GNNs for financial fraud detection, identifies gaps and limitations in existing research, and suggests potential directions for future research.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Review
Computer Science, Artificial Intelligence
Enhao Ning, Changshuo Wang, Huang Zhang, Xin Ning, Prayag Tiwari
Summary: This review provides a detailed overview of occluded person re-identification methods and conducts a systematic analysis and comparison of existing deep learning-based approaches. It offers important theoretical and practical references for future research in the field.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Computer Science, Artificial Intelligence
Jiajun Ma, Songyu Hu, Jianzhong Fu, Gui Chen
Summary: The article presents a novel visual hierarchical attention detector for multi-scale defect location and classification, utilizing texture, semantic, and instance features of defects through a hierarchical attention mechanism, achieving multi-scale defect detection in bearing images with complex backgrounds.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
