Betania Hernández-Ocaña, Adrian García-López, José Hernández-Torruco, Oscar Chávez-Bosquez^*

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1797-1813, 2022, DOI:10.32604/iasc.2022.023570

Abstract The Bacterial Foraging Algorithm (BFOA) is a well-known swarm collective intelligence algorithm used to solve a variety of constraint optimization problems with wide success. Despite its universality, implementing the BFOA may be complex due to the calibration of multiple parameters. Moreover, the Two-Swim Modified Bacterial Foraging Optimization Algorithm (TS-MBFOA) is a state-of-the-art modification of the BFOA which may lead to solutions close to the optimal but with more parameters than the original BFOA. That is why in this paper we present the design using the Unified Modeling Language (UML) and the implementation in the MATLAB platform of a front-end for… More >

Aman Bhaskar¹, Chirag Sharma¹, Khalid Mohiuddin², Aman Singh^1,*, Osman A. Nasr², Mamdooh Alwetaishi³

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3069-3089, 2022, DOI:10.32604/cmc.2022.019866

Abstract Advancement in multimedia technology has resulted in protection against distortion, modification, and piracy. For implementing such protection, we have an existing technique called watermarking but obtaining desired distortion level with sufficient robustness is a challenging task for watermarking in multimedia applications. In the paper, we proposed a smart technique for video watermarking associating meta-heuristic algorithms along with an embedding method to gain an optimized efficiency. The main aim of the optimization algorithm is to obtain solutions with maximum robustness, and which should not exceed the set threshold of quality. To represent the accuracy of the proposed scheme, we employ a… More >

Fatemeh Ahmadi Zeidabadi¹, Sajjad Amiri Doumari¹, Mohammad Dehghani², Zeinab Montazeri³, Pavel Trojovský^4,*, Gaurav Dhiman⁵

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5631-5649, 2022, DOI:10.32604/cmc.2022.021072

Abstract Optimization plays an effective role in various disciplines of science and engineering. Optimization problems should either be optimized using the appropriate method (i.e., minimization or maximization). Optimization algorithms are one of the efficient and effective methods in providing quasi-optimal solutions for these type of problems. In this study, a new algorithm called the Mutated Leader Algorithm (MLA) is presented. The main idea in the proposed MLA is to update the members of the algorithm population in the search space based on the guidance of a mutated leader. In addition to information about the best member of the population, the mutated… More >

R. Manjula Devi¹, M. Premkumar², Pradeep Jangir³, Mohamed Abdelghany Elkotb^4,5, Rajvikram Madurai Elavarasan⁶, Kottakkaran Sooppy Nisar^7,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4803-4827, 2022, DOI:10.32604/cmc.2022.020847

Abstract Optimization is a key technique for maximizing or minimizing functions and achieving optimal cost, gains, energy, mass, and so on. In order to solve optimization problems, metaheuristic algorithms are essential. Most of these techniques are influenced by collective knowledge and natural foraging. There is no such thing as the best or worst algorithm; instead, there are more effective algorithms for certain problems. Therefore, in this paper, a new improved variant of a recently proposed metaphorless Runge-Kutta Optimization (RKO) algorithm, called Improved Runge-Kutta Optimization (IRKO) algorithm, is suggested for solving optimization problems. The IRKO is formulated using the basic RKO and… More >

Fatemeh Ahmadi Zeidabadi¹, Sajjad Amiri Doumari¹, Mohammad Dehghani², Zeinab Montazeri², Pavel Trojovský^3,*, Gaurav Dhiman⁴

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2905-2921, 2022, DOI:10.32604/cmc.2022.019867

Abstract There are many optimization problems in different branches of science that should be solved using an appropriate methodology. Population-based optimization algorithms are one of the most efficient approaches to solve this type of problems. In this paper, a new optimization algorithm called All Members-Based Optimizer (AMBO) is introduced to solve various optimization problems. The main idea in designing the proposed AMBO algorithm is to use more information from the population members of the algorithm instead of just a few specific members (such as best member and worst member) to update the population matrix. Therefore, in AMBO, any member of the… More >

Waqas Haider Bangyal¹, Abdul Hameed¹, Jamil Ahmad², Kashif Nisar^3,*, Muhammad Reazul Haque⁴, Ag. Asri Ag. Ibrahim³, Joel J. P. C. Rodrigues^5,6, M. Adil Khan⁷, Danda B. Rawat⁸, Richard Etengu⁴

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2241-2259, 2022, DOI:10.32604/cmc.2022.017789

Abstract Bat algorithm (BA) is an eminent meta-heuristic algorithm that has been widely used to solve diverse kinds of optimization problems. BA leverages the echolocation feature of bats produced by imitating the bats’ searching behavior. BA faces premature convergence due to its local search capability. Instead of using the standard uniform walk, the Torus walk is viewed as a promising alternative to improve the local search capability. In this work, we proposed an improved variation of BA by applying torus walk to improve diversity and convergence. The proposed. Modern Computerized Bat Algorithm (MCBA) approach has been examined for fifteen well-known benchmark… More >

Adnan Ashraf¹, Abdulwahab Ali Almazroi², Waqas Haider Bangyal^3,*, Mohammed A. Alqarni⁴

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 191-206, 2022, DOI:10.32604/iasc.2022.015810

Abstract Particle Swarm Optimization (PSO) is a well-known extensively utilized algorithm for a distinct type of optimization problem. In meta-heuristic algorithms, population initialization plays a vital role in solving the classical problems of optimization. The population’s initialization in meta-heuristic algorithms urges the convergence rate and diversity, besides this, it is remarkably beneficial for finding the efficient and effective optimal solution. In this study, we proposed an enhanced variation of the PSO algorithm by using a quasi-random sequence (QRS) for population initialization to improve the convergence rate and diversity. Furthermore, this study represents a new approach for population initialization by incorporating the… More >

Fatimah O. Albalawi, Mashael S. Maashi^*

Intelligent Automation & Soft Computing, Vol.28, No.1, pp. 39-52, 2021, DOI:10.32604/iasc.2021.015657

Abstract In the software field, a large number of projects fail, and billions of dollars are spent on these failed projects. Many software projects are also produced with poor quality or they do not exactly meet customers’ expectations. Moreover, these projects may exceed project budget and/or time. The complexity of managing software development projects and the poor selection of software development life cycle (SDLC) models are among the top reasons for such failure. Various SDLC models are available, but no model is considered the best or worst. In this work, we propose a new methodology that solves the SDLC optimization problem… More >

Muhammad Asif Jan^1,*, Yasir Mahmood¹, Hidayat Ullah Khan², Wali Khan Mashwani¹, Muhammad Irfan Uddin³, Marwan Mahmoud⁴, Rashida Adeeb Khanum⁵, Ikramullah⁶, Noor Mast³

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2845-2862, 2021, DOI:10.32604/cmc.2021.015294

Abstract The particle swarm optimization (PSO) algorithm is an established nature-inspired population-based meta-heuristic that replicates the synchronizing movements of birds and fish. PSO is essentially an unconstrained algorithm and requires constraint handling techniques (CHTs) to solve constrained optimization problems (COPs). For this purpose, we integrate two CHTs, the superiority of feasibility (SF) and the violation constraint-handling (VCH), with a PSO. These CHTs distinguish feasible solutions from infeasible ones. Moreover, in SF, the selection of infeasible solutions is based on their degree of constraint violations, whereas in VCH, the number of constraint violations by an infeasible solution is of more importance. Therefore,… More >

Xiaoye Shi^{1, *}, Jin Sun¹, Dongming Li¹, Fei Ding², Zhaowei Zhang¹

CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1373-1384, 2020, DOI:10.32604/cmc.2020.011018

Abstract In this paper, we study the rate-energy tradeoff for wireless simultaneous information and power transfer in full-duplex and half-duplex scenarios. To this end, the weighting function of energy efficiency and transmission rate, as rate-energy tradeoff metric is first introduced and the metric optimization problem is formulated. Applying Karush-Kuhn-Tucker (KKT) conditions for Lagrangian optimality and a series of mathematical approximations, the metric optimization problem can be simplified. The closed-form solution of the power ratio is obtained, building direct relationship between power ratio and the rate-energy tradeoff metric. By choosing power ratio, one can make the tradeoff between information rate and harvested… More >