Littérature scientifique sur le sujet « METAHEURISTIC OPTIMIZATION TECHNIQUES »
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Articles de revues sur le sujet "METAHEURISTIC OPTIMIZATION TECHNIQUES"
Rahman, Md Ashikur, Rajalingam Sokkalingam, Mahmod Othman, Kallol Biswas, Lazim Abdullah et Evizal Abdul Kadir. « Nature-Inspired Metaheuristic Techniques for Combinatorial Optimization Problems : Overview and Recent Advances ». Mathematics 9, no 20 (19 octobre 2021) : 2633. http://dx.doi.org/10.3390/math9202633.
Texte intégralFeitosa Neto, Antonino, Anne Canuto et João Xavier-Junior. « Hybrid Metaheuristics to the Automatic Selection of Features and Members of Classifier Ensembles ». Information 9, no 11 (26 octobre 2018) : 268. http://dx.doi.org/10.3390/info9110268.
Texte intégralMisevičius, Alfonsas, Vytautas Bukšnaitis et Jonas Blonskis. « Kombinatorinis optmizavimas ir metaeuristiniai metodai : teoriniai aspektai ». Informacijos mokslai 42, no 43 (1 janvier 2008) : 213–19. http://dx.doi.org/10.15388/im.2008.0.3417.
Texte intégralSahoo, Rashmi Rekha, et Mitrabinda Ray. « Metaheuristic Techniques for Test Case Generation ». Journal of Information Technology Research 11, no 1 (janvier 2018) : 158–71. http://dx.doi.org/10.4018/jitr.2018010110.
Texte intégralFunes Lora, Miguel Angel, Edgar Alfredo Portilla-Flores, Raul Rivera Blas, Emmanuel Alejandro Merchán Cruz et Manuel Faraón Carbajal Romero. « Metaheuristic techniques comparison to optimize robotic end-effector behavior and its workspace ». International Journal of Advanced Robotic Systems 15, no 5 (1 septembre 2018) : 172988141880113. http://dx.doi.org/10.1177/1729881418801132.
Texte intégralRadhika, Sajja, et Aparna Chaparala. « Optimization using evolutionary metaheuristic techniques : a brief review ». Brazilian Journal of Operations & ; Production Management 15, no 1 (10 mai 2018) : 44–53. http://dx.doi.org/10.14488/bjopm.2018.v15.n1.a17.
Texte intégralAugusto, Adriano, Marlon Dumas, Marcello La Rosa, Sander J. J. Leemans et Seppe K. L. M. vanden Broucke. « Optimization framework for DFG-based automated process discovery approaches ». Software and Systems Modeling 20, no 4 (27 février 2021) : 1245–70. http://dx.doi.org/10.1007/s10270-020-00846-x.
Texte intégralNavarro-Acosta, Jesús Alejandro, Irma D. García-Calvillo, Vanesa Avalos-Gaytán et Edgar O. Reséndiz-Flores. « Metaheuristics and Support Vector Data Description for Fault Detection in Industrial Processes ». Applied Sciences 10, no 24 (21 décembre 2020) : 9145. http://dx.doi.org/10.3390/app10249145.
Texte intégralFidanova, Stefka Stoyanova, et Olympia Nikolaeva Roeva. « Metaheuristic Techniques for Optimization of anE. ColiCultivation Model ». Biotechnology & ; Biotechnological Equipment 27, no 3 (janvier 2013) : 3870–76. http://dx.doi.org/10.5504/bbeq.2012.0136.
Texte intégralTahami, Hesamoddin, et Hengameh Fakhravar. « A Literature Review on Combining Heuristics and Exact Algorithms in Combinatorial Optimization ». European Journal of Information Technologies and Computer Science 2, no 2 (29 avril 2022) : 6–12. http://dx.doi.org/10.24018/compute.2022.2.2.50.
Texte intégralThèses sur le sujet "METAHEURISTIC OPTIMIZATION TECHNIQUES"
Franz, Wayne. « Multi-population PSO-GA hybrid techniques : integration, topologies, and parallel composition ». Springer, 2013. http://hdl.handle.net/1993/23842.
Texte intégralMantilla, Gaviria Iván Antonio. « New Strategies to Improve Multilateration Systems in the Air Traffic Control ». Doctoral thesis, Editorial Universitat Politècnica de València, 2013. http://hdl.handle.net/10251/29688.
Texte intégralMantilla Gaviria, IA. (2013). New Strategies to Improve Multilateration Systems in the Air Traffic Control [Tesis doctoral]. Editorial Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/29688
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Diaz, Leiva Juan Esteban. « Simulation-based optimization for production planning : integrating meta-heuristics, simulation and exact techniques to address the uncertainty and complexity of manufacturing systems ». Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/simulationbased-optimization-for-production-planning-integrating-metaheuristics-simulation-and-exact-techniques-to-address-the-uncertainty-and-complexity-of-manufacturing-systems(9ef8cb33-99ba-4eb7-aa06-67c9271a50d0).html.
Texte intégralJaber, Ahmed. « Hybrid Algorithm for Multi-objective Mixed-integer Non-convex Mechanical Design Optimization Problems ». Thesis, Troyes, 2021. http://www.theses.fr/2021TROY0034.
Texte intégralMulti-objective mixed-integer non-convex non-linear constrained optimization problems that appears in several fields especially in mechanical applications. This thesis aims to develop a new method to solve such problems. Our proposal is a hybridization of the Multi-Criteria Branch-and-Bound (MCBB) algorithm with the Non-dominated Sorting Genetic Algorithm 2 (NSGAII). The proposed approach is furthermore enhanced by new branching strategies designed for MCBB. The constraints are handled using a new proposed constraint handling technique for evolutionary algorithms. Numerical experiments based on statistical assessment are done in this thesis to examine the performance of the new proposed approach. Results show the competitive performance of our algorithm among NSGAII. We propose two applications of our proposed approach: "Search Feasibility" and "Seek Optimality" applications. Both are applied on a real-world state of art 3 stages reducer problem which is formulated in this thesis to a bi-objective problem to meet the requirement of ISO standards on calculation of load capacity of gears
Benaichouche, Ahmed Nasreddine. « Conception de métaheuristiques d'optimisation pour la segmentation d'images : application aux images IRM du cerveau et aux images de tomographie par émission de positons ». Thesis, Paris Est, 2014. http://www.theses.fr/2014PEST1106/document.
Texte intégralImage segmentation is the process of partitioning a digital image into homogeneous non-overlapped regions with respect to some characteristics, such as gray value, motion, texture, etc. It is used in various applications like medical imaging, objects detection, biometric system, remote sensing, robot navigation, video surveillance, etc. The success of the machine vision system depends heavily on its performance, because characteristics and decisions are extracted and taken from its result. The first image segmentation algorithms were introduced in the 70's. Since then, various techniques and methods were experimented to improve the results. Nevertheless, up till now, no method produces a perfect result for a wide variety of images. Metaheuristics are a high level procedure designed to solve hard optimization problems. These problems are in general characterized by their incomplete, uncertain or noised data, or faced to low computing capacity. Metaheuristics have been extremely successful in a wide variety of fields and demonstrate significant results. This is due to the fact that they can applied to solve any problem which can be formulated as an optimization problem. These methods are, mainly, inspired from physics (simulated annealing), biology (evolutionary algorithms), or ethology (particle swarm optimization, ant colony optimization).In recent years, metaheuristics are starting to be exploited to solve segmentation problems with varying degrees of success and allow to consider the problem with different perspectives. Bearing this in mind, we propose in this work three segmentation and post-segmentation approaches based on mono or multiobjective optimization metaheuristics. The proposed methods were evaluated on databases containing synthetic images, simulated MRI images, real MRI images and PET images. The obtained results show the efficiency of the proposed ideas
Rahmani, Younes. « The Multi-product Location-Routing Problem with Pickup and Delivery ». Thesis, Université de Lorraine, 2015. http://www.theses.fr/2015LORR0331/document.
Texte intégralIn the framework of Location-Routing Problem (LRP), the main idea is to combine strategic decisions related to the choice of processing centers with tactical and operational decisions related to the allocation of customers to selected processing centers and computing the associated routes. This thesis proposes a new location-routing model to solve problems which are coming from logistics networks, that became nowadays increasingly complex due to the need of resources sharing, in order to integrate the constraints of sustainable development and fuels price, which is increasing irreversibly. More precisely, three aspects have been integrated to generalize the classical LRP models already existed in the literature: 1) pickup and delivery aspect, 2) multi-product aspect, and 3) the possibility to use the processing centers as intermediate facilities in routes. We studied two logistics schemes gives us two new location-routing models: (i) MPLRP-PD (Multi-product LRP with pickup and delivery), which can be viewed as an extension of the vehicle routing problem with pick-up and delivery, including a tactical decision related to the location of processing centers (node with pick-up and delivery), and (ii) 2E-MPLRP-PD (Two-echelon multi-product LRP with pickup and delivery), which is a generalization of the two-echelon LRP. Both models were formalized by mixed integer linear programming (MIP). Solving techniques, based on heuristic methods, clustering approach and meta-heuristic techniques have been proposed to solve the MPLRP-PD and the 2E-MPLRP-PD. The benchmarks from the literature were generalized to test and to validate the proposed algorithms
Ayachi, Hajjem Imen. « Techniques avancées d'optimisation pour la résolution du problème de stockage de conteneurs dans un port ». Thesis, Ecole centrale de Lille, 2012. http://www.theses.fr/2012ECLI0003/document.
Texte intégralThe loading and unloading of containers and their temporary storage in the container terminal are the most important and complex operation in seaport terminals. It is highly inter-related with the routing of yard crane and truck and their costs increased significantly especially without an efficient terminal management. To improve this process, an efficiency decision for the container storage space allocation must be taken.In this thesis, we studied the container storage problem (CSP). It falls into the category of NP hard and NP complete problems. CSP consists on finding the most suitable storage location for incoming containers that minimizes rehandling operations of containers during their transfer to the ship, truck or train. In fact, the wait time of customer trucks, the transfer time of yard crane and the Ship turnaround time are advantageously reduced.Generally, this problem is studied considering a single container type. However, this does not stand the problem under its real-life statement as there are multiple container types that should be considered, (refrigerated, open side, empty, dry, open top and tank). Often, containers arrive at the port dynamically over time and have an uncertain departure date (ship delayed, a ship down, delayed arrival of customer trucks…). Indeed, CSP must be studied in dynamic aspectThe objective of this thesis is to study Static CSP for a single and various container type and dynamic CSP for ONE and several container types and to propose solutions for each of them. Genetic algorithm and Harmony Search algorithm are used to solve these problems and we compare the results of each approach with the LIFO algorithm
El, Dor Abbas. « Perfectionnement des algorithmes d'optimisation par essaim particulaire : applications en segmentation d'images et en électronique ». Phd thesis, Université Paris-Est, 2012. http://tel.archives-ouvertes.fr/tel-00788961.
Texte intégralLepagnot, Julien. « Conception de métaheuristiques pour l'optimisation dynamique : application à l'analyse de séquences d'images IRM ». Phd thesis, Université Paris-Est, 2011. http://tel.archives-ouvertes.fr/tel-00674754.
Texte intégralCooren, Yann. « Perfectionnement d'un algorithme adaptatif d'Optimisation par Essaim Particulaire : application en génie médical et en électronique ». Phd thesis, Université Paris-Est, 2008. http://tel.archives-ouvertes.fr/tel-00462106.
Texte intégralLivres sur le sujet "METAHEURISTIC OPTIMIZATION TECHNIQUES"
Ponce-Ortega, José María, et Luis Germán Hernández-Pérez. Optimization of Process Flowsheets through Metaheuristic Techniques. Cham : Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-91722-1.
Texte intégralPonce-Ortega, José María, et Luis Germán Hernández-Pérez. Optimization of Process Flowsheets through Metaheuristic Techniques. Springer, 2018.
Trouver le texte intégralPonce-Ortega, José María, et Luis Germán Hernández-Pérez. Optimization of Process Flowsheets through Metaheuristic Techniques. Springer, 2019.
Trouver le texte intégralSwamy, M. N. S., et Ke-Lin Du. Search and Optimization by Metaheuristics : Techniques and Algorithms Inspired by Nature. Birkhauser Verlag, 2016.
Trouver le texte intégralSwamy, M. N. S., et Ke-Lin Du. Search and Optimization by Metaheuristics : Techniques and Algorithms Inspired by Nature. Birkhäuser, 2018.
Trouver le texte intégralSwamy, M. N. S., et Ke-Lin Du. Search and Optimization by Metaheuristics : Techniques and Algorithms Inspired by Nature. Springer, 2016.
Trouver le texte intégralChapitres de livres sur le sujet "METAHEURISTIC OPTIMIZATION TECHNIQUES"
Ponce-Ortega, José María, et Luis Germán Hernández-Pérez. « Metaheuristic Optimization Programs ». Dans Optimization of Process Flowsheets through Metaheuristic Techniques, 27–51. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91722-1_3.
Texte intégralRao, R. V., et S. Patel. « Optimization of Robot Path Planning Using Advanced Optimization Techniques ». Dans Metaheuristic Algorithms in Industry 4.0, 83–126. Boca Raton : CRC Press, 2021. http://dx.doi.org/10.1201/9781003143505-5.
Texte intégralAbdel-Basset, Mohamed, Ripon K. Chakrabortty et Reda Mohamed. « Metaheuristic Algorithms for Healthcare ». Dans Application of Advanced Optimization Techniques for Healthcare Analytics, 25–36. New York : CRC Press, 2023. http://dx.doi.org/10.1201/9781003325574-2.
Texte intégralDeroussi, Laurent, Nathalie Grangeon et Sylvie Norre. « Optimization of Logistics Systems Using Metaheuristic-Based Hybridization Techniques ». Dans Metaheuristics, 381–405. Cham : Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-45403-0_14.
Texte intégralPonce-Ortega, José María, et Luis Germán Hernández-Pérez. « Optimization of Industrial Process 1 ». Dans Optimization of Process Flowsheets through Metaheuristic Techniques, 79–90. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91722-1_6.
Texte intégralPonce-Ortega, José María, et Luis Germán Hernández-Pérez. « Optimization of Industrial Process 2 ». Dans Optimization of Process Flowsheets through Metaheuristic Techniques, 91–97. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91722-1_7.
Texte intégralHe, Xing-Shi, Qin-Wei Fan, Mehmet Karamanoglu et Xin-She Yang. « Comparison of Constraint-Handling Techniques for Metaheuristic Optimization ». Dans Lecture Notes in Computer Science, 357–66. Cham : Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22744-9_28.
Texte intégralKarnik, Niharika, et Pankaj Dhatrak. « Optimization Techniques and Algorithms for Dental Implants – A Comprehensive Review ». Dans Metaheuristic Algorithms in Industry 4.0, 261–82. Boca Raton : CRC Press, 2021. http://dx.doi.org/10.1201/9781003143505-12.
Texte intégralPonce-Ortega, José María, et Luis Germán Hernández-Pérez. « Interlinking Between Process Simulators and Optimization Programs ». Dans Optimization of Process Flowsheets through Metaheuristic Techniques, 53–73. Cham : Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91722-1_4.
Texte intégralAbdel-Basset, Mohamed, Ripon K. Chakrabortty et Reda Mohamed. « Contribution of Metaheuristic Approaches for Feature Selection Techniques ». Dans Application of Advanced Optimization Techniques for Healthcare Analytics, 103–24. New York : CRC Press, 2023. http://dx.doi.org/10.1201/9781003325574-6.
Texte intégralActes de conférences sur le sujet "METAHEURISTIC OPTIMIZATION TECHNIQUES"
Serrano Elena, Antonio. « METAHEURISTIC ANALYSIS IN REVERSE LOGISTICS OF WASTE ». Dans CIT2016. Congreso de Ingeniería del Transporte. Valencia : Universitat Politècnica València, 2016. http://dx.doi.org/10.4995/cit2016.2016.3163.
Texte intégralLoubna, Kritele, El Beqal Asmae, Zorkani Izeddine et Benhala Bachir. « Metaheuristic-based Optimization Techniques for Optimal Analog Filter Sizing ». Dans 2018 International Conference on Electronics, Control, Optimization and Computer Science (ICECOCS). IEEE, 2018. http://dx.doi.org/10.1109/icecocs.2018.8610525.
Texte intégralSingh, Rajendra Bahadur, Anurag Singh Baghel et Ayush Agarwal. « A review on VLSI floorplanning optimization using metaheuristic algorithms ». Dans 2016 International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT). IEEE, 2016. http://dx.doi.org/10.1109/iceeot.2016.7755508.
Texte intégralKoudela, Pavel, et Juraj Chalmovský. « Automation of calibration process adopting metaheuristic optimization method ». Dans The 13th international scientific conference “Modern Building Materials, Structures and Techniques”. Vilnius Gediminas Technical University, 2019. http://dx.doi.org/10.3846/mbmst.2019.142.
Texte intégralGunal, Ozen, Mustafa Akpinar et Kevser Ovaz Akpinar. « Performance Evaluation of Metaheuristic Optimization Techniques in Insulation Problem ». Dans 2022 8th International Conference on Information Technology Trends (ITT). IEEE, 2022. http://dx.doi.org/10.1109/itt56123.2022.9863959.
Texte intégralLeite da Silva, Armando M., Joao Guilherme de C. Costa, Kascilene G. Machado et Carlos H. V. Moraes. « Spare transformers optimization using Monte Carlo simulation and metaheuristic techniques ». Dans 2015 18th International Conference on Intelligent System Application to Power Systems (ISAP). IEEE, 2015. http://dx.doi.org/10.1109/isap.2015.7325578.
Texte intégralSarapan, Waranyu, Nonthakorn Boonrakchat, Ashok Paudel, Terapong Boonraksa, Promphak Boonraksa et Boonruang Marungsri. « Optimal Energy Management in Smart House using Metaheuristic Optimization Techniques ». Dans 2022 International Conference on Power, Energy and Innovations (ICPEI). IEEE, 2022. http://dx.doi.org/10.1109/icpei55293.2022.9986889.
Texte intégralWadi, Mohammed, Wisam Elmasry, Abdulfetah Shobole, Mehmet Rida Tur, Ramazan Bayindir et Hossein Shahinzadeh. « Wind Energy Potential Approximation with Various Metaheuristic Optimization Techniques Deployment ». Dans 2021 7th International Conference on Signal Processing and Intelligent Systems (ICSPIS). IEEE, 2021. http://dx.doi.org/10.1109/icspis54653.2021.9729389.
Texte intégralBoualem, Nasri, Mostefai Lotfi, Guessoum Abderrezak, Benikhlef Abdelhak, Zemalache Meguenni Kadda et Tahar Mohammed. « Metaheuristic optimization techniques of a sliding-mode controller gains applied to quadrotor ». Dans PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGY AND MULTIDISCIPLINE (ICATAM) 2021 : “Advanced Technology and Multidisciplinary Prospective Towards Bright Future” Faculty of Advanced Technology and Multidiscipline. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0118909.
Texte intégralKavaliauskas, Donatas, et Leonidas Sakalauskas. « Conceptual model of productivity bot for smart construction planning ». Dans The 13th international scientific conference “Modern Building Materials, Structures and Techniques”. Vilnius Gediminas Technical University, 2019. http://dx.doi.org/10.3846/mbmst.2019.003.
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