Titlebook: Constraint Handling in Metaheuristics and Applications; Anand J. Kulkarni,Efrén Mezura-Montes,Ganesh Krish Book 2021 The Editor(s) (if app

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Sutchin R. Patel MD,Stephen Y. Nakada MDhe large bandwidth available at mmwave frequencies. But it is challenging to estimate the channel for mmwave wireless communication systems with hybrid precoding, since the number of radio frequency chains are much smaller as compared to a number of antennas. Due to limited scattering, the Beam spac

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Marcel Hruza MD,Jens Rassweiler MDate genetic algorithm running on a smartphone. We examine these techniques on one particular problem: the tourist trip design problem. This problem selects a set of points of interest that matches tourist preferences to bring a personalized trip plan. Our points of interest are focused on Mexico Cit

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978-981-33-6712-8The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor

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Anand J. Kulkarni,Efrén Mezura-Montes,Ganesh KrishDiscusses core and underlying mechanisms of different constraint handling approaches.Provides a platform for validation of novel constraint handling approaches and a complete reference to the in-depth

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滔滔不绝地讲

Economics of Using Biocidal Surfaces,est problems have been successfully solved by using the proposed algorithm. The CI-PL approach produced competent and sufficiently robust results solving unconstrained, constrained, and engineering problems. The associated strengths, weaknesses, and possible real-world extensions are also discussed.

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An Improved Cohort Intelligence with Panoptic Learning Behavior for Solving Constrained Problems,est problems have been successfully solved by using the proposed algorithm. The CI-PL approach produced competent and sufficiently robust results solving unconstrained, constrained, and engineering problems. The associated strengths, weaknesses, and possible real-world extensions are also discussed.

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Keqin Jiang,Yuzhou Zhang,Linqiang Panct the algorithms’ performances considerably. In this study, some of the well-known strategies are incorporated into particle swarm optimization algorithms (PSO). The performance of the PSO algorithm is examined through several benchmarks, constrained problems, and the results discussed comprehensively.