Review
Computer Science, Information Systems
Maha Nssibi, Ghaith Manita, Ouajdi Korbaa
Summary: The main objective of feature selection is to improve learning performance by selecting concise and informative feature subsets. This paper explores nature-inspired metaheuristic methods for the feature selection problem, with a focus on representation and search algorithms. An analysis of various advanced approach types and their advantages and disadvantages is provided, along with guidance for conducting future research effectively in this field.
COMPUTER SCIENCE REVIEW
(2023)
Article
Engineering, Civil
Saeid Kazemzadeh Azad, Sina Kazemzadeh Azad
Summary: Benchmarking is an important part of developing efficient structural optimization techniques. Current benchmarking of new algorithms often relies on classic test examples that are not challenging for modern optimization algorithms. Furthermore, the available optimization results for new test examples are usually not accurately comparable due to the lack of information about algorithm performance and inconsistencies between studies. Therefore, there is a need to develop new standard test suites that include easily reproducible challenging test examples and allow for rigorous and comparable performance evaluation of algorithms.
Article
Computer Science, Artificial Intelligence
Jeng-Shyang Pan, Pei Hu, Vaclav Snasel, Shu-Chuan Chu
Summary: This article comprehensively investigates the current state-of-the-art of engineering applications utilizing binary metaheuristic algorithms. It categorizes the surveyed work based on application scenarios and solution encoding, providing detailed descriptions of these algorithms to guide researchers in choosing appropriate methods for related applications. The article identifies current issues and challenges, and discusses the need to address novel binary algorithms, transfer functions, benchmark functions, time-consuming problems, and application integration in the future.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Computer Science, Artificial Intelligence
Guo Zhou, Yongquan Zhou, Wu Deng, Shihong Yin, Yunhui Zhang
Summary: This paper provides a comprehensive survey on the recent advances in Teaching-learning-based optimization (TLBO) algorithm, revealing intriguing challenges and suggesting potential future research directions.
Article
Computer Science, Information Systems
Mohammad Amiriebrahimabadi, Najme Mansouri
Summary: This paper reviews and compares feature selection algorithms based on Whale Optimization Algorithm (WOA). Most variations of WOA focus on improving the learning process, while some introduce new parameters or operators. The paper also discusses current issues and challenges, and identifies future research directions.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Yongquan Zhou, Yan Shi, Yuanfei Wei, Qifang Luo, Zhonghua Tang
Summary: The 0-1 knapsack problem is a classic variant of knapsack problems, aiming to select items with maximum total profit within the constraints of the knapsack's capacity. It has various real-world applications such as resource distribution and portfolio optimization. This study reviews the basic theory and algorithms of 0-1 knapsack, proposes nature-inspired metaheuristic algorithms, and categorizes existing problems into 6 types based on different coding methods, providing a comprehensive overview.
Article
Engineering, Industrial
Erkan Erdemir
Summary: The study developed a hybrid algorithm, HSSAOA, by combining the exploration phase of AOA with the position update part of SSA. The algorithm was tested on 22 benchmark functions in three different groups and compared with 7 well-known algorithms. HSSAOA achieved the best results in 16 benchmark functions in each group and showed a statistically significant difference compared to other algorithms.
INTERNATIONAL JOURNAL OF INDUSTRIAL ENGINEERING COMPUTATIONS
(2023)
Article
Computer Science, Interdisciplinary Applications
Setyo Tri Windras Mara, Rachmadi Norcahyo, Panca Jodiawan, Luluk Lusiantoro, Achmad Pratama Rifai
Summary: This article provides a survey on the popular metaheuristic framework, ALNS, discussing its basic concepts and synthesizing the state-of-the-art research through an analysis of scientific publications. It also offers discussions on future research directions.
COMPUTERS & OPERATIONS RESEARCH
(2022)
Article
Automation & Control Systems
Danial Yazdani, Mohammad Nabi Omidvar, Ran Cheng, Jurgen Branke, Trung Thanh Nguyen, Xin Yao
Summary: This study provides a comprehensive review of existing benchmarks and investigates their shortcomings in capturing different problem features. It then proposes a highly configurable benchmark suite capable of generating problem instances with various characteristics.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Mathematics
Juan Li, Qing An, Hong Lei, Qian Deng, Gai-Ge Wang
Summary: Levy flight is a random walk mechanism used in metaheuristic algorithms to solve NP-hard problems. It exhibits a movement pattern of large and small jumps in local areas, allowing it to escape local optima and expand the search area. Research shows the superiority of Levy flight-based metaheuristic algorithms in various fields.
Article
Computer Science, Artificial Intelligence
Fatma A. Hashim, Abdelazim G. Hussien
Summary: In recent years, various metaheuristic algorithms have been introduced in engineering and scientific fields to solve real-life optimization problems. This study proposes a novel nature-inspired metaheuristic algorithm called Snake Optimizer (SO), which imitates the mating behavior of snakes to tackle different optimization tasks. Experimental results demonstrate the effectiveness and efficiency of SO compared to other algorithms in terms of exploration-exploitation balance and convergence speed.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Sunday Oyinlola Ogundoyin, Ismaila Adeniyi Kamil
Summary: This paper provides a comprehensive review of optimization methods and their applications in fog computing, including taxonomy of optimization techniques, glossary of optimization metrics, and classification of evaluation environments. The distribution of relevant publications, threats to validity, challenges in existing literature, and future research trends are also discussed.
SWARM AND EVOLUTIONARY COMPUTATION
(2021)
Article
Computer Science, Theory & Methods
Blesson Varghese, Nan Wang, David Bermbach, Cheol-Ho Hong, Eyal De Lara, Weisong Shi, Christopher Stewart
Summary: Edge computing is the future of the internet, leveraging computing resources near users, sensors, and data stores to provide faster services. Benchmarking the performance of such complex systems is crucial, as their operational conditions are expected to change significantly. Edge performance benchmarking has gained momentum as a research field in the past five years.
ACM COMPUTING SURVEYS
(2022)
Review
Environmental Sciences
B. Sri Revathi
Summary: The sustainability of the earth relies on renewable energy. Accurate forecasting of renewable energy generation is essential for grid dependability and reducing energy market risks and costs. Machine learning algorithms and physical models combined with cloud pictures are commonly used to forecast solar radiation on a global scale.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Engineering, Industrial
Baoyu Liao, Shaojun Lu, Tao Jiang, Xing Zhu
Summary: Ship maintenance service optimisation is important for improving the competitiveness of shipbuilding enterprises. This paper investigates a scheduling problem considering various factors and proposes mathematical models and algorithms to solve it. The performance of the proposed methods is validated through computational experiments.
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
(2022)
Article
Operations Research & Management Science
Ester Gutierrez, Sebastian Lozano
Summary: This paper assesses the relative efficiency of the forest sector in 28 EU/EFTA countries during the period 2010-2015 using DEA, and identifies factors that influence efficiency. The results can provide guidance for roundwood production.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Mathematics, Applied
Manuel Arana-Jimenez, M. Carmen Sanchez-Gil, Sebastian Lozano
Summary: This paper discusses the problem of efficiency assessment using Data Envelopment Analysis (DEA) when the input and output data are given as fuzzy sets. The authors propose a fuzzy extension of the measure of inefficiency proportions and provide fuzzy input and output targets.
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
(2022)
Article
Computer Science, Software Engineering
Beatriz Bernardez, Amador Duran, Jose A. Parejo, Natalia Juristo, Antonio Ruiz-Cortes
Summary: This study found that software engineering students showed improved conceptual modeling performance in terms of quality and productivity after practicing mindfulness. These findings indicate the positive impact of mindfulness on enhancing students' performance in software engineering tasks.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2022)
Article
Computer Science, Software Engineering
Juan C. Alonso, Alberto Martin-Lopez, Sergio Segura, Jose Maria Garcia, Antonio Ruiz-Cortes
Summary: In this article, the authors present ARTE, an approach for automated extraction of realistic test data for web APIs from knowledge bases. ARTE leverages natural language processing, search-based, and knowledge extraction techniques to automatically search for realistic test inputs based on the API specification. The evaluation results demonstrate the potential of ARTE for enhancing web API testing tools and achieving a higher level of automation.
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING
(2023)
Article
Management
Sebastian Lozano, Somayeh Khezri
Summary: This study proposes a new approach for evaluating the efficiency of decision-making units with interval data, introducing a potential-based measure of efficiency. The methodology is demonstrated using a dataset related to the performance of branches of an insurance company in Iran and compared with existing methods.
IMA JOURNAL OF MANAGEMENT MATHEMATICS
(2023)
Article
Hospitality, Leisure, Sport & Tourism
Julio Lozano-Ramirez, Manuel Arana-Jimenez, Sebastian Lozano
Summary: This study evaluates the sustainability efficiency of tourism in 27 countries in the European Union from 2015 to 2019 using data analysis envelopment methodology and various economic, social, and environmental indicators. The results provide valuable information on sustainable tourism practices and support the challenging task of rebuilding the sector and resuming the pre-pandemic trend of increasing tourism sustainability.
CURRENT ISSUES IN TOURISM
(2023)
Article
Computer Science, Information Systems
Sergio Laso, Javier Berrocal, Pablo Fernandez, Antonio Ruiz-Cortes, Juan M. Murillo
Summary: The increasing capabilities of mobile devices have led to the emergence of new paradigms exploiting them. This paper presents a framework called Perses, which allows the creation of virtual scenarios with multiple heterogeneous mobile devices to evaluate distributed mobile applications. The framework was evaluated against a real deployment and integrated into a DevOps methodology.
PERVASIVE AND MOBILE COMPUTING
(2022)
Article
Computer Science, Theory & Methods
Antonio Quina-Mera, Pablo Fernandez, Jose Maria Garcia, Antonio Ruiz-Cortes
Summary: GraphQL is a query language and execution engine proposed as an alternative to improve data access problems and versioning of APIs. This article presents a systematic mapping study of 84 primary studies to analyze the trends and knowledge gaps in the GraphQL field. The study concludes that GraphQL adoption is increasing as a strong alternative for implementing APIs, but more empirical evidence collection is needed in industry and government studies.
ACM COMPUTING SURVEYS
(2023)
Article
Operations Research & Management Science
Sebastian Lozano, Gabriel Villa
Summary: This paper introduces a multi-objective fixed-sum output (FSO) approach that considers factors such as the total number of medals awarded. The approach aims to set all output targets as close as possible to their ideal values. A secondary goal of minimizing the sum of absolute changes in the number of medals is also considered. The proposed approach has been applied to the results of the Tokyo 2020 Olympic Games and compared with FSO and non-FSO DEA methods.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Theory & Methods
Margarita Cruz, Beatriz Bernardez, Amador Duran, Cathy Guevara-Vega, Antonio Ruiz-Cortes
Summary: The main goal of this article is to provide a systematic tool-supported approach for the specification and reporting of changes in replications of empirical studies in Computer Science. The developed artifact includes a metamodel, templates and linguistic patterns, and a model-based software tool. A multiple case study with 9 families of empirical studies was conducted to validate the approach, revealing some initial limitations. The proposed method seems to be applicable not only in Computer Science but also in other research areas.
Correction
Computer Science, Theory & Methods
Margarita Cruz, Beatriz Bernardez, Amador Duran, Cathy Guevara-Vega, Antonio Ruiz-Cortes
Article
Computer Science, Software Engineering
Sergio Laso, Javier Berrocal, Pablo Fernandez, Jose Maria Garcia, Jose M. Garcia-Alonso, Juan M. Murillo, Antonio Ruiz-Cortes, Schahram Dustdar
Summary: The massive deployment of Internet-connected devices has resulted in an increase in data collection for companies to enhance their decision-making processes. To efficiently manage limited resources and cater to multiple users' interest in the same data, the cloud-to-things continuum can be utilized to execute analytics closer to the data source, optimizing infrastructure consumption and data circulation.
IEEE INTERNET COMPUTING
(2022)
Article
Management
Sebastian Lozano
Summary: This paper presents a model that combines fixed-sum DEA technology with bargaining methods to deal with input or output variables with fixed total amounts. By computing the Nash bargaining solution and using an enhanced efficiency measure, efficient analysis for all units is achieved.
OMEGA-INTERNATIONAL JOURNAL OF MANAGEMENT SCIENCE
(2023)
Article
Engineering, Industrial
Belarmino Adenso-Diaz, Sebastian Lozano
Summary: This paper presents a DEA approach to assess the efficiency of company's shipments and haulers. It benchmarks shipments first against all shipments of the same hauler and then against all shipments of all haulers. The efficiency of each shipment and hauler can be determined. The proposed approach is useful to assess price quotes and negotiate better prices.
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE-OPERATIONS & LOGISTICS
(2023)
Correction
Computer Science, Theory & Methods
Margarita Cruz, Beatriz Bernardez, Amador Duran, Cathy Guevara-Vega, Antonio Ruiz-Cortes