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Gotowe bibliografie tematyczne / METAHEURISTIC APPROACH

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Artykuły w czasopismach

Gotowa bibliografia na temat „METAHEURISTIC APPROACH”

Autor: Grafiati

Data publikacji: 11 września 2023

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Artykuły w czasopismach na temat "METAHEURISTIC APPROACH"

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Laudis, Lalin L., and Amit Kumar Sinha. "Metaheuristic Approach for VLSI 3D-Floorplanning." International Journal of Scientific Research 2, no. 12 (2012): 202–3. http://dx.doi.org/10.15373/22778179/dec2013/62.

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LEE, YOUNG CHOON, JAVID TAHERI, and ALBERT Y. ZOMAYA. "A PARALLEL METAHEURISTIC FRAMEWORK BASED ON HARMONY SEARCH FOR SCHEDULING IN DISTRIBUTED COMPUTING SYSTEMS." International Journal of Foundations of Computer Science 23, no. 02 (2012): 445–64. http://dx.doi.org/10.1142/s0129054112400229.

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A large number of optimization problems have been identified as computationally challenging and/or intractable to solve within a reasonable amount of time. Due to the NP-hard nature of these problems, in practice, heuristics account for the majority of existing algorithms. Metaheuristics are one very popular type of heuristics used for many of these optimization problems. In this paper, we present a novel parallel-metaheuristic framework, which effectively enables to devise parallel metaheuristics, particularly with heterogeneous metaheuristics. The core component of the proposed framework is

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Bajenaru, Victor, Steven Lavoie, Brett Benyo, Christopher Riker, Mitchell Colby, and James Vaccaro. "Recommender System Metaheuristic for Optimizing Decision-Making Computation." Electronics 12, no. 12 (2023): 2661. http://dx.doi.org/10.3390/electronics12122661.

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We implement a novel recommender system (RS) metaheuristic framework within a nonlinear NP-hard decision-making problem, for reducing the solution search space before high-burden computational steps are performed. Our RS-based metaheuristic supports consideration of comprehensive evaluation criteria, including estimations of the potential solution set’s optimality, diversity, and feedback/preference of the end-user, while also being fully compatible with additional established RS evaluation metrics. Compared to prior Operations Research metaheuristics, our RS-based metaheuristic allows for (1)

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Rosłon, Jerzy Hubert, and Janusz Edward Kulejewski. "A hybrid approach for solving multi-mode resource-constrained project scheduling problem in construction." Open Engineering 9, no. 1 (2019): 7–13. http://dx.doi.org/10.1515/eng-2019-0006.

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AbstractPractical problems in construction can be easily qualified as NP-hard (non-deterministic, polynomial-time hard) problems. The time needed for solving these problems grows exponentially with the increase of the problem’s size – this is why mathematical and heuristic methods do not enable finding solutions to complicated construction problems within an acceptable period of time. In the view of many authors, metaheuristic algorithms seem to be the most appropriate measures for scheduling and task sequencing. However even metaheuristic approach does not guarantee finding the optimal soluti

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Correia, Sérgio D., Marko Beko, Luis A. Da Silva Cruz, and Slavisa Tomic. "Elephant Herding Optimization for Energy-Based Localization." Sensors 18, no. 9 (2018): 2849. http://dx.doi.org/10.3390/s18092849.

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This work addresses the energy-based source localization problem in wireless sensors networks. Instead of circumventing the maximum likelihood (ML) problem by applying convex relaxations and approximations, we approach it directly by the use of metaheuristics. To the best of our knowledge, this is the first time that metaheuristics are applied to this type of problem. More specifically, an elephant herding optimization (EHO) algorithm is applied. Through extensive simulations, the key parameters of the EHO algorithm are optimized such that they match the energy decay model between two sensor n

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Talatahari, Babak, Mahdi Azizi, Siamak Talatahari, Mohamad Tolouei, and Pooya Sareh. "Crystal structure optimization approach to problem solving in mechanical engineering design." Multidiscipline Modeling in Materials and Structures 18, no. 1 (2022): 1–23. http://dx.doi.org/10.1108/mmms-10-2021-0174.

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PurposeIn this paper, the authors aim to examine and comparatively evaluate a recently-developed metaheuristic called crystal structure algorithm (CryStAl) – which is inspired by the symmetries in the internal structure of crystalline solids – in solving engineering mechanics and design problems.Design/methodology/approachA total number of 20 benchmark mathematical functions are employed as test functions to evaluate the overall performance of the proposed method in handling various functions. Moreover, different classical and modern metaheuristic algorithms are selected from the optimization

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Cruz-Duarte, Jorge M., José C. Ortiz-Bayliss, Iván Amaya, Yong Shi, Hugo Terashima-Marín, and Nelishia Pillay. "Towards a Generalised Metaheuristic Model for Continuous Optimisation Problems." Mathematics 8, no. 11 (2020): 2046. http://dx.doi.org/10.3390/math8112046.

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Metaheuristics have become a widely used approach for solving a variety of practical problems. The literature is full of diverse metaheuristics based on outstanding ideas and with proven excellent capabilities. Nonetheless, oftentimes metaheuristics claim novelty when they are just recombining elements from other methods. Hence, the need for a standard metaheuristic model is vital to stop the current frenetic tendency of proposing methods chiefly based on their inspirational source. This work introduces a first step to a generalised and mathematically formal metaheuristic model, which can be u

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Barraza, Juan, Luis Rodríguez, Oscar Castillo, Patricia Melin, and Fevrier Valdez. "A New Hybridization Approach between the Fireworks Algorithm and Grey Wolf Optimizer Algorithm." Journal of Optimization 2018 (May 27, 2018): 1–18. http://dx.doi.org/10.1155/2018/6495362.

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The main aim of this paper is to present a new hybridization approach for combining two powerful metaheuristics, one inspired by physics and the other one based on bioinspired phenomena. The first metaheuristic is based on physics laws and imitates the explosion of the fireworks and is called Fireworks Algorithm; the second metaheuristic is based on the behavior of the grey wolf and belongs to swarm intelligence methods, and this method is called the Grey Wolf Optimizer algorithm. For this work we studied and analyzed the advantages of the two methods and we propose to enhance the weakness of

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Yaghini, Masoud, Mohsen Momeni, and Mohammadreza Sarmadi. "A DIMMA-Based Memetic Algorithm for 0-1 Multidimensional Knapsack Problem Using DOE Approach for Parameter Tuning." International Journal of Applied Metaheuristic Computing 3, no. 2 (2012): 43–55. http://dx.doi.org/10.4018/jamc.2012040104.

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Multidimensional 0-1 Knapsack Problem (MKP) is a well-known integer programming problems. The objective of MKP is to find a subset of items with maximum value satisfying the capacity constraints. A Memetic algorithm on the basis of Design and Implementation Methodology for Metaheuristic Algorithms (DIMMA) is proposed to solve MKP. DIMMA is a new methodology to develop a metaheuristic algorithm. The Memetic algorithm is categorized as metaheuristics and is a particular class of evolutionary algorithms. The parameters of the proposed algorithm are tuned by Design of Experiments (DOE) approach. D

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Wahab, Hala Bahjat Abdul, Suhad Malallah Kadhem, and Estabraq Abdul Redaa Kadhim. "Proposed Approach for Elliptic Curve Cryptography Based on Metaheuristic Algorithms." International Journal of Scientific Research 2, no. 10 (2012): 1–5. http://dx.doi.org/10.15373/22778179/oct2013/33.

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