Article
Computer Science, Artificial Intelligence
M. Bagheri, Ali Ebrahimnejad, S. Razavyan, F. Hosseinzadeh Lotfi, N. Malekmohammadi
Summary: This paper proposes a DEA-based approach to solve the multi-objective shortest path problem with fuzzy parameters, converting it into a Fuzzy Shortest Path Problem that can be solved using existing algorithms.
COMPLEX & INTELLIGENT SYSTEMS
(2021)
Article
Mathematics
Haoran Zhu, Yunhe Wang, Zhiqiang Ma, Xiangtao Li
Summary: This study explores the performance of different swarm intelligence algorithms in path-planning for uninhabited combat air vehicles (UCAV) and finds that the Spider Monkey Optimization algorithm is more effective.
Article
Management
Michael S. Hughes, Brian J. Lunday, Jeffrey D. Weir, Kenneth M. Hopkinson
Summary: This research introduces the MSPP-PD model to balance agent routing efficiency with group vulnerability. It examines the distinguishability of different MSPP-PD variants in optimal agent routing solutions and the impact of penalty function metrics on identifying these solutions.
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
(2021)
Article
Engineering, Marine
Charis Ntakolia, Dimitrios V. V. Lyridis
Summary: This study proposes a hybrid approach of Ant Colony Optimization algorithm with fuzzy logic and clustering methods to solve multiobjective path planning problems in swarm USVs. The performance of the ACO algorithm is explored by integrating fuzzy logic to handle multiple contradicting objectives and generate quality solutions. The operational areas for each USV in the swarm are designed using a comparative evaluation of three popular clustering algorithms. A comparative evaluation is also conducted among ACO and fuzzy inference systems to solve the multiobjective path planning problem.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Multidisciplinary
Debora Di Caprio, Ali Ebrahimnejad, Hamidreza Alrezaamiri, Francisco J. Santos-Arteaga
Summary: This paper presents a fuzzy-based Ant Colony Optimization algorithm for solving shortest path problems with different types of fuzzy weights. The algorithm approximates the weights of fuzzy paths using the a-cut method and compares them using a signed distance function. The results show that the fuzzy-based enhanced ACO algorithm outperforms other metaheuristic algorithms in terms of convergence time.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Computer Science, Artificial Intelligence
Lihua Lin, Chuzheng Wu, Li Ma
Summary: The shortest path problem in a fuzzy network involves determining the optimal path between specified source and destination vertices, utilizing fuzzy logic to handle uncertainties. The two main challenges in this context are calculating path length using fuzzy addition and comparing path lengths denoted by fuzzy parameters. Graded mean integration technique of triangular fuzzy numbers and genetic algorithm are commonly used to address these challenges.
COMPLEX & INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Gokhan Ozcelik
Summary: This paper examines the performances of multi-criteria decision-making methods and an optimization model in solving multi-attribute shortest path problems. The authors compare different techniques in terms of computational effort and results in a fuzzy environment, providing insights regarding the effectiveness and performance of the methods discussed in the solution process.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Engineering, Marine
Charis Ntakolia, Dimitrios Lyridis
Summary: The increased use of unmanned surface vehicles (USVs) in complex environments has created the need for novel path planning approaches that can effectively address multi-objective path planning problems. This study focuses on extending the use of Ant Colony Optimization (ACO) by incorporating fuzzy inference systems and conducting a comparative evaluation of different scenarios. The results show that ACO with Mamdani achieves better solution quality, ACO with RMSE has higher convergence speed, and ACO with TSK strikes a balance between convergence speed and solution quality. Therefore, each approach can be considered for multi-objective path planning of USVs depending on the application requirements.
Article
Engineering, Marine
Charis Ntakolia, Dimitrios Lyridis
Summary: This study aims to extend the application of Ant Colony Optimization (ACO) to multi-objective path planning problems by using fuzzy inference systems and the root mean square error criterion. Comparative evaluation of different approaches in solving multi-objective USV path planning problems showed that ACO with Mamdani achieved the best solution quality, ACO with RMSE had higher convergence speed, and ACO with TSK balanced better between convergence speed and solution quality.
Article
Engineering, Marine
Charis Ntakolia, Dimitrios Lyridis
Summary: Advancements in robotic motion and computer vision have led to the increased use of automated and unmanned vehicles in complex environments. Among these, unmanned surface vehicles (USVs) have gained attention for their potential in maritime transportation. Traditional single-objective path planning approaches may not suffice in dynamic environments, hence the need for multi-objective path planning. The study introduced and evaluated a swarm intelligence graph-based pathfinding algorithm (SIGPA) with fuzzy logic integration, comparing it to two popular fuzzy inference systems (Mamdani and Takagi-Sugeno-Kang). Results showed each methodology could offer advantages depending on application needs, with SIGPA remaining reliable, SIGPAF-M generating better paths, and SIGPAF-TSK achieving a better balance between solution quality and computation time.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2021)
Article
Multidisciplinary Sciences
Zhicheng Yan, Qibing Jin, Yang Zhang, Zeyu Wang, Ziming Li
Summary: This paper proposes a multi-objective harris hawk optimization algorithm based on blank angle region enhanced search (BARESMOHHO) to address the issues of low precision, low search efficiency, and being easy to fall into local optimization. The algorithm initializes the population using chaotic mapping, adjusts the classification level to find low-density regions faster, symmetrically distributes the number of archives at different levels for uniform distribution of individuals in the target space, and strengthens the search for non-individual regions in the division process. The effectiveness of the algorithm is verified through comparisons with known classical functions on test functions.
Article
Engineering, Multidisciplinary
N. Ganesh, Uvaraja Ragavendran, Kanak Kalita, Paras Jain, Xiao-Zhi Gao
Summary: This paper combines high-fidelity finite element method (FEM) with metaheuristic optimization algorithms to propose a method for optimizing composite plates. The study found that the performance of this method in multi-objective Pareto optimization is comparable to NSGA-III.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2021)
Article
Computer Science, Information Systems
Sneha Kamble, Prashant Bhilwar, B. R. Chandavarkar
Summary: In this study, a Fuzzy-based Takagi and Sugeno Objective Function (FTSOF) is proposed for selecting the best path, which uses fuzzy technology to deal with imprecise or distorted attribute values. The experimental results show that FTSOF outperforms other existing techniques in terms of packet delivery ratio, latency, network setup time, and control message overhead.
Article
Computer Science, Artificial Intelligence
Yun Hou, Guosheng Hao, Yong Zhang, Feng Gu, Wenyang Xu
Summary: This paper proposes a multi-objective discrete particle swarm optimization algorithm to solve the particle routing problem in distributed particle filters. Experimental results show that the algorithm is highly competitive and can provide multiple high-quality Pareto optimal solutions.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Theory & Methods
S. C. M. S. De Sirisuriya, T. G. Fernando, M. K. A. Ariyaratne
Summary: This paper describes the importance of path finding and the utilization of optimization techniques in solving this problem. By comparing the performance of different algorithms and considering the generation of test cases, it emphasizes the significance of automatic test case generation.
Article
Energy & Fuels
Shafiqur Rehman, Salman A. Khan
Article
Computer Science, Artificial Intelligence
Salman A. Khan, Amjad Mahmood
NEURAL COMPUTING & APPLICATIONS
(2019)
Article
Computer Science, Information Systems
Amjad Mahmood, Salman A. Khan, Fawzi Albalooshi, Noor Awwad
Article
Computer Science, Artificial Intelligence
Amani Saad, Salman A. Khan, Amjad Mahmood
SWARM AND EVOLUTIONARY COMPUTATION
(2018)
Article
Computer Science, Artificial Intelligence
S. Rehman, S. S. Ali, S. A. Khan
APPLIED ARTIFICIAL INTELLIGENCE
(2018)
Article
Computer Science, Artificial Intelligence
Shafiqur Rehman, Salman A. Khan
APPLIED ARTIFICIAL INTELLIGENCE
(2019)
Article
Green & Sustainable Science & Technology
Shafiqur Rehman, Salman A. Khan, Luai M. Alhems
Review
Computer Science, Hardware & Architecture
Muhammad Hassan Nasir, Salman A. Khan, Muhammad Mubashir Khan, Mahawish Fatima
Summary: This paper presents a systematic review of swarm intelligence approaches deployed in intrusion detection in various attack surfaces and domains between 2010 and 2020. It categorizes the SI approaches according to their applicability in improving different aspects of intrusion detection and discusses the features of datasets used in experimentation. The study aims to help researchers assess the capabilities and limitations of SI algorithms in identifying security threats and challenges, as well as differentiating SI-based IDS from traditional ones.
Article
Chemistry, Multidisciplinary
Salman A. Khan, Kashif Iqbal, Nazeeruddin Mohammad, Rehan Akbar, Syed Saad Azhar Ali, Ammar Ahmed Siddiqui
Summary: This paper proposes a new evaluation metric for email spam detection based on fuzzy logic concept, and it confirms the effectiveness through empirical analysis and extrinsic evaluation.
APPLIED SCIENCES-BASEL
(2022)
Article
Chemistry, Multidisciplinary
Shafiqur Rehman, Salman A. Khan, Luai M. Alhems
APPLIED SCIENCES-BASEL
(2020)
Article
Engineering, Mechanical
Shafiqur Rehman, Salman A. Khan, Luai M. Alhems
Proceedings Paper
Computer Science, Theory & Methods
Salman A. Khan, Mostafa I. H. Abd-El-Barr
PROCEEDINGS 2018 INTERNATIONAL CONFERENCE ON COMPUTING SCIENCES AND ENGINEERING (ICCSE)
(2018)
Article
Computer Science, Theory & Methods
Shafiqur Rehman, Salman A. Khan
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS
(2017)
Article
Computer Science, Interdisciplinary Applications
Amjad Mahmood, Salman A. Khan