Topic
Discrete optimization
About: Discrete optimization is a research topic. Over the lifetime, 4598 publications have been published within this topic receiving 158297 citations. The topic is also known as: discrete optimisation.
Papers published on a yearly basis
Papers
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TL;DR: In order to overcome the premature phenomenon of a discrete bat algorithm, the modified neighborhood operator is proposed and the results indicate that the improved bat algorithm outperforms all the other alternatives in most cases.
28 citations
TL;DR: The Kohonen map is introduced, that orders its neurons according to topological features of the data sets to be trained with, that can be called a topology-preserving feature map and can be used to solve general visualization problems of data mapping into a lower dimensional representation.
Abstract: This paper describes the application of self-organizing neural networks on the analysis and visualization of multidimensional data sets. First, a mathematical description of cluster analysis, dimensionality reduction, and topological ordering is given taking these methods as problems of discrete optimization. Then, the Kohonen map is introduced, that orders its neurons according to topological features of the data sets to be trained with. For this reason, it can also be called a topology-preserving feature map.
28 citations
Journal Article•
TL;DR: A complete survey on partiole swarm optimization is presented in aspect of mechanism, feature, improvements and applications, including multi-objective, constrained,rete and dynamic optimization.
Abstract: A complete survey on partiole swarm optimization (PSO) is presented in aspect of mechanism,feature,improvements and applications.Especially,the studies on PSO aiming at complex environment are introduced,including multi-objective,constrained,discrete and dynamic optimization.The future research direction and contents are pointed out.
28 citations
TL;DR: Results show that the proposed ACOFRS is an alternative method for performing global optimization in phase equilibrium calculations of multicomponent systems and it outperformed other stochastic optimization methods such as Particle Swarm Optimization, Differential Evolution and Genetic Algorithms.
28 citations
TL;DR: The findings show that the impact of imperfect orthogonality is not non-negligible, along with the intra-SF interference and the coverage probability is significantly improved when the location of relay is optimized.
Abstract: In this work, the performance evaluation and the optimization of dual-hop LoRa network are investigated. In particular, the coverage probability (Pcov) of edge end-devices (EDs) is computed in closed-form expressions under various fading channels, i.e., Nakagami- $m$ and Rayleigh fading. The Pcov under Nakagami- $m$ fading is computed in the approximated closed-form expressions; the Pcov under Rayleigh fading, on the other hand, is calculated in the exact closed-form expressions. In addition, we also investigate the impact of different kinds of interference on the performance of the Pcov, i.e., intra-SF interference, inter-SF interference (or capture effect) and both intra- and inter-SF interference. Our findings show that the impact of imperfect orthogonality is not non-negligible, along with the intra-SF interference. Moreover, based on the proposed mathematical framework, we formulate an optimization problem, which finds the optimal location of the relay to maximize the coverage probability. Since it is a mixed integer program with a non-convex objective function, we decompose the original problem with discrete optimization variables into sub-problems with a convex feasible set. After that, each sub-problem is effectively solved by utilizing the gradient descent approach. Monte Carlo simulations are supplied to verify the correctness of our mathematical framework. In addition, the results manifest that our proposed optimization algorithm converges rapidly, and the coverage probability is significantly improved when the location of relay is optimized.
28 citations