نتایج جستجو برای: metaheuristic and genetic algorithm
تعداد نتایج: 16968207 فیلتر نتایج به سال:
Abstract This study proposes the Fire Hawk Optimizer (FHO) as a novel metaheuristic algorithm based on foraging behavior of whistling kites, black kites and brown falcons. These birds are termed Hawks considering specific actions they perform to catch prey in nature, specifically by means setting fire. Utilizing proposed algorithm, numerical investigation was conducted 233 mathematical test fun...
Nature-inspired algorithms such as Particle Swarm Optimization and Firefly Algorithm are among the most powerful algorithms for optimization. In this paper, we intend to formulate a new metaheuristic algorithm by combining Lévy flights with the search strategy via the Firefly Algorithm. Numerical studies and results suggest that the proposed Lévy-flight firefly algorithm is superior to existing...
proposing a robust designed facility location is one of the most effective ways to hedge against unexpected disruptions and failures in a transportation network system. this paper considers the combined facility location/network design problem with regard to transportation link disruptions and develops a mixed integer linear programming formulation to model it. with respect to the probability o...
Metaheuristic algorithms will gain more and more popularity in the future as optimization problems are increasing in size and complexity. In order to record experiences and allow project to be replicated, a standard process as a methodology for designing and implementing metaheuristic algorithms is necessary. To the best of the authors’ knowledge, no methodology has been proposed in literature ...
Cryptology is a thriving research area of great practical importance. It is a fundamental building block of communications security. Metaheuristic optimisation techniques such as simulated annealing and genetic algorithms have found successful application in a huge number of fields. However, their application to leading edge industrial-strength cryptology has been slight. The power of metaheuri...
The human has always been to up to the best in everything, And this perfectionism has led to the creation of optimization methods. The goal of optimization is to determine the variables to find the best acceptable answer to the limitations in a problem, so that the objective function is a minimum or a maximum. Metaheuristic algorithms are one of inaccurate optimization methods that inspired by ...
This paper details the optimisation of bulk material port handling systems through the use of a metaheuristic based approach. The effective management of port systems requires effective solutions for the design, operation and maintenance of these facilities. This has to be achieved through a reduction in financial costs, and an increase in the utilisation of equipment and other resources. The o...
In this paper, we propose a hybrid algorithm combining two different metaheuristic methods, “Genetic Algorithms (GA)” and “Sperm Swarm Optimization (SSO)”, for the global optimization of multimodal benchmarks functions. The proposed Hybrid Genetic Algorithm Sperm (HGASSO) operates based on incorporates concepts from GA SSO in which generates individuals new iteration not only by crossover mutat...
Optimal selection of interdependent IT Projects for implementation in multi periods has been challenging in the framework of real option valuation. This paper presents a mathematical optimization model for multi-stage portfolio of IT projects. The model optimizes the value of the portfolio within a given budgetary and sequencing constraints for each period. These sequencing constraints are due ...
Producing clear and intelligible layouts of hierarchical digraphs knows a renewed interest in information visualization. Recent experimental results show that metaheuristics are well-adapted methods for this problem. In this paper, we develop a new Hybridized Genetic Algorithm for arc crossing minimization. It follows the basic scheme of a GA with two major differences: problem-based crossovers...
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