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Bee Colony Optimization - part II: The application survey [PDF]
Yugoslav Journal of Operations Research, 2015 Bee Colony Optimization (BCO) is a meta-heuristic method based on foraging habits of honeybees. This technique was motivated by the analogy found between the natural behavior of bees searching for food and the behavior of optimization algorithms
Teodorović Dušan +2 more
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Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem
Applications of Modelling and Simulation, 2023 The evolutionary algorithm has been extensively used to solve a range of combinatorial optimization problems. The adaptability of evolutionary algorithm mechanisms provides diverse approaches to handle combinatorial optimization challenges.
Anniza Hamdan +4 more
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Química Nova, 2001 Combinatorial Chemistry has become a very efficient methodology in drug research. Recent progress in combinatorial synthesis performed both in solid and solution phase have led to a change in the paradigm for the identification and optimization of lead ...
Ricardo L. Araújo Dias +1 more
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Combinatorial Optimization Problems and Metaheuristics: Review, Challenges, Design, and Development
Applied Sciences, 2021 In the past few decades, metaheuristics have demonstrated their suitability in addressing complex problems over different domains. This success drives the scientific community towards the definition of new and better-performing heuristics and results in ...
Fernando Peres, M. Castelli
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Discrete Applied Mathematics, 2005 This report summarizes the meeting on Combinatorial Optimization where new and promising developments in the field were discussed ...
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Hysteresis in Combinatorial Optimization Problems
Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2021 Hysteresis is a physical phenomenon reflected in macroscopic observables of materials that are subjected to external perturbations. For example, magnetic hysteresis is observed in ferromagnetic metals such as iron, nickel and cobalt in the presence of a ...
Yuling Guan +4 more
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Graph Learning for Combinatorial Optimization: A Survey of State-of-the-Art
Data Science and Engineering, 2021 Graphs have been widely used to represent complex data in many applications, such as e-commerce, social networks, and bioinformatics. Efficient and effective analysis of graph data is important for graph-based applications.
Yun Peng, Byron Choi, Jianliang Xu
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Highly connected orientations from edge-disjoint rigid subgraphs
Forum of Mathematics, PiWe give an affirmative answer to a long-standing conjecture of Thomassen, stating that every sufficiently highly connected graph has a k-vertex-connected orientation. We prove that a connectivity of order $O(k^2)$ suffices.
Dániel Garamvölgyi +3 more
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The Combinatorial ANT System for Dynamic Combinatorial Optimization Problems
Revista de Matemática: Teoría y Aplicaciones, 2012 En este articulo es presentado un algoritmo distribuido basado en conceptos de los Sistemas de Hormiga, llamado Sistema Combinatorio de Hormigas, para resolver problemas de optimización combinatoria dinámicos.
Jose Aguilar
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Bird Mating Optimizer for Combinatorial Optimization Problems
IEEE Access, 2020 The bird mating optimizer is a new metaheuristic algorithm that was originally proposed to solve continuous optimization problems with a very promising performance.
Anas Arram +3 more
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