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  • Open Access

    ARTICLE

    Migration Algorithm: A New Human-Based Metaheuristic Approach for Solving Optimization Problems

    Pavel Trojovský*, Mohammad Dehghani

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.2, pp. 1695-1730, 2023, DOI:10.32604/cmes.2023.028314 - 26 June 2023

    Abstract This paper introduces a new metaheuristic algorithm called Migration Algorithm (MA), which is helpful in solving optimization problems. The fundamental inspiration of MA is the process of human migration, which aims to improve job, educational, economic, and living conditions, and so on. The mathematical modeling of the proposed MA is presented in two phases to empower the proposed approach in exploration and exploitation during the search process. In the exploration phase, the algorithm population is updated based on the simulation of choosing the migration destination among the available options. In the exploitation phase, the algorithm… More >

  • Open Access

    ARTICLE

    Language Education Optimization: A New Human-Based Metaheuristic Algorithm for Solving Optimization Problems

    Pavel Trojovský1,*, Mohammad Dehghani1, Eva Trojovská1, Eva Milkova2

    CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.2, pp. 1527-1573, 2023, DOI:10.32604/cmes.2023.025908 - 06 February 2023

    Abstract In this paper, based on the concept of the NFL theorem, that there is no unique algorithm that has the best performance for all optimization problems, a new human-based metaheuristic algorithm called Language Education Optimization (LEO) is introduced, which is used to solve optimization problems. LEO is inspired by the foreign language education process in which a language teacher trains the students of language schools in the desired language skills and rules. LEO is mathematically modeled in three phases: (i) students selecting their teacher, (ii) students learning from each other, and (iii) individual practice, considering… More > Graphic Abstract

    Language Education Optimization: A New Human-Based Metaheuristic Algorithm for Solving Optimization Problems

  • Open Access

    ARTICLE

    Skill Optimization Algorithm: A New Human-Based Metaheuristic Technique

    Hadi Givi1, Marie Hubalovska2,*

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 179-202, 2023, DOI:10.32604/cmc.2023.030379 - 22 September 2022

    Abstract Metaheuristic algorithms are widely used in solving optimization problems. In this paper, a new metaheuristic algorithm called Skill Optimization Algorithm (SOA) is proposed to solve optimization problems. The fundamental inspiration in designing SOA is human efforts to acquire and improve skills. Various stages of SOA are mathematically modeled in two phases, including: (i) exploration, skill acquisition from experts and (ii) exploitation, skill improvement based on practice and individual effort. The efficiency of SOA in optimization applications is analyzed through testing this algorithm on a set of twenty-three standard benchmark functions of a variety of unimodal, More >

  • Open Access

    ARTICLE

    Optimization of Head Cluster Selection in WSN by Human-Based Optimization Techniques

    Hajer Faris1, Musaria Karim Mahmood2, Osama Ahmad Alomari3,*, Ashraf Elnagar4

    CMC-Computers, Materials & Continua, Vol.72, No.3, pp. 5643-5661, 2022, DOI:10.32604/cmc.2022.026228 - 21 April 2022

    Abstract Wireless sensor networks (WSNs) are characterized by their ability to monitor physical or chemical phenomena in a static or dynamic location by collecting data, and transmit it in a collaborative manner to one or more processing centers wirelessly using a routing protocol. Energy dissipation is one of the most challenging issues due to the limited power supply at the sensor node. All routing protocols are large consumers of energy, as they represent the main source of energy cost through data exchange operation. Cluster-based hierarchical routing algorithms are known for their good performance in energy conservation… More >

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