• A new method to solve linear programming problems in the environment of picture fuzzy sets 

  Akram, Muhammad; Ullah, Iftikhar; Allahviranloo, Tofigh (Iranian Journal of Fuzzy Systems, 2022)

  Picture fuzzy set is characterized by neutral membership function along with the membership and non-membership functions, and is, therefore, more general than the intuitionistic fuzzy set which is only characterized by ...

• A reinforcement learning-based metaheuristic algorithm for solving global optimization problems 

  Seyyedabbasi, Amir (Elsevier, 2023)

  The purpose of this study is to utilize reinforcement learning in order to improve the performance of the Sand Cat Swarm Optimization algorithm (SCSO). In this paper, we propose a novel algorithm for the solution of global ...

• Fuzzy generalized fractional power series technique for simulating fuzzy fractional relaxation problem 

  Ebdalifar, Khatereh; Allahviranloo, Tofigh; Rostamy-Malkhalifeh, Mohsen; Behzadi, Mohammad Hassan (Springer link, 2022)

  In this paper, the fuzzy generalized fractional power series method is proposed to obtain the numerical solutions of a class of fuzzy fractional relaxation problems. For this purpose, the fuzzy generalized fractional power ...

• Slime mould algorithm: a comprehensive survey of ıts variants and applications 

  Gharehchopogh, Farhad Soleimanian; Ucan, Alaettin; Ibrikci, Turgay; Arasteh, Bahman; Isik, Gultekin (SPRINGER, 2023)

  Meta-heuristic algorithms have a high position among academic researchers in various fields, such as science and engineering, in solving optimization problems. These algorithms can provide the most optimal solutions for ...

• Solution of initial-value problem for linear third-order fuzzy differential equations 

  Muhammad, Ghulam; Allahviranloo, Tofigh; Pedrycz, Witold (SPRINGER HEIDELBERG, 2022)

  Every real-world physical problem is inherently based on uncertainty. It is essential to model the uncertainty then solve, analyze and interpret the result one encounters in the world of vagueness. Generally, science and ...

• Data preprocessing strategy in constructing convolutional neural network classifier based on constrained particle swarm optimization with fuzzy penalty function 

  Zhou, Kun; Oh, Sung-Kwun; Pedrycz, Witold; Qiu, Jianlong (Elsevier, 2022)

  Convolutional neural networks (CNNs) have attracted increasing attention in recent years because of their powerful abilities to extract and represent spatial/temporal information. However, for general data, its features ...

• A new maximal flow algorithm for solving optimization problems with linguistic capacities and flows 

  Akram, Muhammad; Habib, Amna; Allahviranloo, Tofigh (ELSEVIER SCIENCE INC, 2022)

  The maximal flow problems (MFPs) are among the most significant optimization problems in network flow theory with widespread and diverse applications. To represent qualitative aspects of uncertainty in the maximal flow ...

• An improved farmland fertility algorithm with hyper-heuristic approach for solving travelling salesman problem 

  Gharehchopogh, Farhad Soleimanian; Abdollahzadeh, Benyamin; Arasteh, Bahman (TECH SCIENCE PRESS, 2022)

  ravelling Salesman Problem (TSP) is a discrete hybrid optimization problem considered NP-hard. TSP aims to discover the shortest Hamilton route that visits each city precisely once and then returns to the starting point, ...

• Classical and intelligent methods in model extraction and stabilization of a dual-axis reaction wheel pendulum: a comparative study 

  Tavakol Aghaei, Vahid; Akbulut, Batuhan Ekin; Tan, Deniz; Allahviranloo, Tofigh; Fernandez Gamiz, Unai; Noeiaghdam, Samad; Bezci, Yüksel Ediz (Elsevier B.V., 2022)

  Controlling underactuated open-loop unstable systems is challenging. In this study, first, both nonlinear and linear models of a dual-axis reaction wheel pendulum (DA-RWP) are extracted by employing Lagrangian equations ...

• Fuzzy control problem via random multi-valued equations in symmetric F-n-NLS 

  Saadati, Reza; Allahviranloo, Tofigh; O'Regan, Donal; Alshammari, Fehaid Salem (MDPI, 2022)

  To study an uncertain case of a control problem, we consider the symmetric F-n-NLS which is induced by a dynamic norm inspired by a random norm, distribution functions, and fuzzy sets. In this space, we consider a random ...

• Program source code comprehension by module clustering using combination of discretized gray wolf and genetic algorithms 

  Arasteh, Bahman; Abdi, Mohammad; Bouyer, Asgarali (Elsevier Ltd, 2022)

  Maintenance is a critical and costly phase of software lifecycle. Understanding the structure of software will make it much easier to maintain the software. Clustering the modules of software is regarded as a useful reverse ...

• Clustered design-model generation from a program source code using chaos-based metaheuristic algorithms 

  Arasteh, Bahman (Springer Science and Business Media Deutschland GmbH, 2022)

  Comprehension of the structure of software will facilitate maintaining the software more efficiently. Clustering software modules, as a reverse engineering technique, is assumed to be an effective technique in extracting ...

• Maximizing coverage and maintaining connectivity in WSN and decentralized IoT: an efficient metaheuristic-based method for environment-aware node deployment 

  Nematzadeh, Sajjad; Torkamanian-Afshar, Mahsa; Seyyedabbasi, Amir; Kiani, Farzad (Springer Science and Business Media Deutschland GmbH, 2022)

  The node deployment problem is a non-deterministic polynomial time (NP-hard). This study proposes a new and efficient method to solve this problem without the need for predefined circumstances about the environments ...

• FIP: A fast overlapping community-based influence maximization algorithm using probability coefficient of global diffusion in social networks 

  Bouyer, Asgarali; Ahmadi Beni, Hamid; Arasteh, Bahman; Aghaee, Zahra; Ghanbarzadeh, Reza (Elsevier Ltd, 2023)

  Influence maximization is the process of identifying a small set of influential nodes from a complex network to maximize the number of activation nodes. Due to the critical issues such as accuracy, stability, and time ...

• WOASCALF: A new hybrid whale optimization algorithm based on sine cosine algorithm and levy flight to solve global optimization problems 

  Seyyedabbasi, Amir (Elsevier Ltd, 2022)

  In recent years, researchers have been focused on solving optimization problems in order to determine the global optimum. Increasing the dimension of a problem increases its computational cost and complexity as well. In ...

• Optimal data transmission and pathfinding for WSN and decentralized IoT systems using I-GWO and Ex-GWO algorithms 

  Seyyedabbasi, Amir; Kiani, Farzad; Allahviranloo, Tofigh; Fernandez-Gamiz, Unai; Noeiaghdam, Samad (Elsevier B.V., 2023)

  Efficient resource use is a very important issue in wireless sensor networks and decentralized IoT-based systems. In this context, a smooth pathfinding mechanism can achieve this goal. However, since this problem is a ...

• A source-code aware method for software mutation testing using artificial bee colony algorithm 

  Arasteh, Bahman; Imanzadeh, Parisa; Arasteh, Keyvan; Gharehchopogh, Farhad Soleimanian; Zarei, Bagher (SPRINGER, 2022)

  The effectiveness of software test data relates to the number of found faults by the test data. Software mutation test is used to evaluate the effectiveness of the software test methods and is one of the challenging fields ...

• A smart and mechanized agricultural application: From cultivation to harvest 

  Kiani, Farzad; Randazzo, Giovanni; Yelmen, İlkay; Seyyedabbasi, Amir; Nematzadeh, Sajjad; Anka, Fateme Ayşin; Erenel, Fahri (MDPI, 2022)

  Food needs are increasing day by day, and traditional agricultural methods are not responding efficiently. Moreover, considering other important global challenges such as energy sufficiency and migration crises, the need ...

• Sand Cat swarm optimization: a nature-inspired algorithm to solve global optimization problems 

  Seyyedabbasi, Amir; Kiani, Farzad (Springer, 2022)

  This study proposes a new metaheuristic algorithm called sand cat swarm optimization (SCSO) which mimics the sand cat behavior that tries to survive in nature. These cats are able to detect low frequencies below 2 kHz and ...

• Traxtor: An automatic software test suit generation method inspired by imperialist competitive optimization algorithms 

  Arasteh, Bahman; Hosseini, Seyed Mohamad Javad (Springer, 2022)

  Software testing refers to a process which improves the quality of software systems and also is one of time and cost consuming stages in software development. Hence, software test automation is regarded as a solution which ...

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