Harsh Goud¹, Prakash Chandra Sharma², Kashif Nisar^3,7,*, Muhammad Reazul Haque⁴, Ag. Asri Ag. Ibrahim³, Narendra Singh Yadav², Pankaj Swarnkar⁵, Manoj Gupta⁶, Laxmi Chand⁶

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 3481-3492, 2022, DOI:10.32604/cmc.2022.019764

Abstract Robots in the medical industry are becoming more common in daily life because of various advantages such as quick response, less human interference, high dependability, improved hygiene, and reduced aging effects. That is why, in recent years, robotic aid has emerged as a blossoming solution to many challenges in the medical industry. In this manuscript, meta-heuristics (MH) algorithms, specifically the Firefly Algorithm (FF) and Genetic Algorithm (GA), are applied to tune PID controller constraints such as Proportional gain Kp Integral gain Ki and Derivative gain Kd. The controller is used to control Mobile Robot System (MRS) at the required set… More >

T. S. Balaji^1,2, S. Srinivasan^3,*, S. Prasanna Bharathi⁴, B. Ramesh⁵

Computer Systems Science and Engineering, Vol.43, No.1, pp. 291-304, 2022, DOI:10.32604/csse.2022.023269

Abstract Due to the advanced developments in communication technologies, Internet of vehicles and vehicular adhoc networks (VANET) offers numerous opportunities for effectively managing transportation problems. On the other, the cloud environment needs to disseminate the emergency message to the vehicles which are consistently distributed on the roadway so that every vehicle gets the messages from closer vehicles in a straightforward way. To resolve this issue, clustering and routing techniques can be designed using computational intelligence approaches. With this motivation, this paper presents a new type-2 fuzzy sets based clustering with metaheuristic optimization based routing (T2FSC-MOR) technique for secure communication in VANET.… More >

Souad Larabi-Marie-Sainte¹, Taiseer Abdalla Elfadil Eisa², Fahd N. Al-Wesabi^3,4, Amani Abdulrahman Albraikan⁵, Manar Ahmed Hamza^6,*, Abdelwahed Motwakel⁶, Ishfaq Yaseen⁶, Mesfer Al Duhayyim⁷

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1293-1308, 2022, DOI:10.32604/cmc.2022.024585

Abstract Snake Robots (SR) have been successfully deployed and proved to attain bio-inspired solutions owing to its capability to move in harsh environments, a characteristic not found in other kinds of robots (like wheeled or legged robots). Underwater Snake Robots (USR) establish a bioinspired solution in the domain of underwater robotics. It is a key challenge to increase the motion efficiency in underwater robots, with respect to forwarding speed, by enhancing the locomotion method. At the same time, energy efficiency is also considered as a crucial issue for long-term automation of the systems. In this aspect, the current research paper concentrates… More >

Mohammed Hadwan^1,2,3,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5545-5559, 2022, DOI:10.32604/cmc.2022.024512

Abstract A real-life problem is the rostering of nurses at hospitals. It is a famous nondeterministic, polynomial time (NP) -hard combinatorial optimization problem. Handling the real-world nurse rostering problem (NRP) constraints in distributing workload equally between available nurses is still a difficult task to achieve. The international shortage of nurses, in addition to the spread of COVID-19, has made it more difficult to provide convenient rosters for nurses. Based on the literature, heuristic-based methods are the most commonly used methods to solve the NRP due to its computational complexity, especially for large rosters. Heuristic-based algorithms in general have problems striking the… More >

Prachi Agrawal¹, Khalid Alnowibet², Ali Wagdy Mohamed^3,4,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2847-2868, 2022, DOI:10.32604/cmc.2022.023126

Abstract This paper presents a novel application of metaheuristic algorithms for solving stochastic programming problems using a recently developed gaining sharing knowledge based optimization (GSK) algorithm. The algorithm is based on human behavior in which people gain and share their knowledge with others. Different types of stochastic fractional programming problems are considered in this study. The augmented Lagrangian method (ALM) is used to handle these constrained optimization problems by converting them into unconstrained optimization problems. Three examples from the literature are considered and transformed into their deterministic form using the chance-constrained technique. The transformed problems are solved using GSK algorithm and… More >

D. Nageswari^1,*, N. Kalaiarasi², G. Geethamahalakshmi¹

Computer Systems Science and Engineering, Vol.41, No.2, pp. 493-509, 2022, DOI:10.32604/csse.2022.020539

Abstract Power loss and voltage uncertainty are the major issues prevalently faced in the design of distribution systems. But such issues can be resolved through effective usage of networking reconfiguration that has a combination of Distributed Generation (DG) units from distribution networks. In this point of view, optimal placement and sizing of DGs are effective ways to boost the performance of power systems. The optimum allocation of DGs resolves various problems namely, power loss, voltage profile improvement, enhanced reliability, system stability, and performance. Several research works have been conducted to address the distribution system problems in terms of power loss, energy… More >

Olutomilayo Olayemi Petinrin¹, Faisal Saeed², Xiangtao Li¹, Fahad Ghabban², Ka-Chun Wong^1,3,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4745-4762, 2022, DOI:10.32604/cmc.2022.020523

Abstract Bioactive compounds in plants, which can be synthesized using N-arylation methods such as the Buchwald-Hartwig reaction, are essential in drug discovery for their pharmacological effects. Important descriptors are necessary for the estimation of yields in these reactions. This study explores ten metaheuristic algorithms for descriptor selection and model a voting ensemble for evaluation. The algorithms were evaluated based on computational time and the number of selected descriptors. Analyses show that robust performance is obtained with more descriptors, compared to cases where fewer descriptors are selected. The essential descriptor was deduced based on the frequency of occurrence within the 50 extracted… More >

Prachi Agrawal¹, Khalid Alnowibet², Talari Ganesh¹, Adel F. Alrasheedi², Hijaz Ahmad³, Ali Wagdy Mohamed^4,5,*

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 817-829, 2022, DOI:10.32604/cmc.2022.019685

Abstract Recent years witness a great deal of interest in artificial intelligence (AI) tools in the area of optimization. AI has developed a large number of tools to solve the most difficult search-and-optimization problems in computer science and operations research. Indeed, metaheuristic-based algorithms are a sub-field of AI. This study presents the use of the metaheuristic algorithm, that is, water cycle algorithm (WCA), in the transportation problem. A stochastic transportation problem is considered in which the parameters supply and demand are considered as random variables that follow the Weibull distribution. Since the parameters are stochastic, the corresponding constraints are probabilistic. They… More >

Arkan Kh Shakr Sabonchi^*, Bahriye Akay

Computer Systems Science and Engineering, Vol.39, No.1, pp. 87-106, 2021, DOI:10.32604/csse.2021.05365

Abstract This paper presents state-of-art cryptanalysis studies on attacks of the substitution and transposition ciphers using various metaheuristic algorithms. Traditional cryptanalysis methods employ an exhaustive search, which is computationally expensive. Therefore, metaheuristics have attracted the interest of researchers in the cryptanalysis field. Metaheuristic algorithms are known for improving the search for the optimum solution and include Genetic Algorithm, Simulated Annealing, Tabu Search, Particle Swarm Optimization, Differential Evolution, Ant Colony, the Artificial Bee Colony, Cuckoo Search, and Firefly algorithms. The most important part of these various applications is deciding the fitness function to guide the search. This review presents how these algorithms… More >

Said Ali Hassan¹, Khalid Alnowibet², Miral H. Khodeir¹, Prachi Agrawal³, Adel F. Alrasheedi², Ali Wagdy Mohamed^4,5,*

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 849-871, 2021, DOI:10.32604/cmc.2021.018389

Abstract Commercial airline companies are continuously seeking to implement strategies for minimizing costs of fuel for their flight routes as acquiring jet fuel represents a significant part of operating and managing expenses for airline activities. A nonlinear mixed binary mathematical programming model for the airline fuel task is presented to minimize the total cost of refueling in an entire flight route problem. The model is enhanced to include possible discounts in fuel prices, which are performed by adding dummy variables and some restrictive constraints, or by fitting a suitable distribution function that relates prices to purchased quantities. The obtained fuel plan… More >