Titlebook: Decision Science in Action; Theory and Applicati Kusum Deep,Madhu Jain,Said Salhi Book 2019 Springer Nature Singapore Pte Ltd. 2019 Optimiz

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J. H. M. de Vries,N. F. J. M. DuifIn this paper, we consider the class of fractional interval-valued programming problems. Utilizing the concept of LU optimal solution, the solution concepts of such type of problems have been discussed. Further, the Fritz John and KKT optimality conditions for the nondifferentiable fractional interval-valued functions have also been established.

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Arnold Bakker,Toon Taris,Jan de JongeAchieving stability of biped robot during walking is a tough task. In this paper, we generate polynomial cubic spline for ankle joints, hip joints, and upper body so that the resulting walk is stable. Stability is assured by calculating zero momentum point with largest stability margin in Matlabs.

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Effect of Upper Body Motion on Biped Robot Stability,Achieving stability of biped robot during walking is a tough task. In this paper, we generate polynomial cubic spline for ankle joints, hip joints, and upper body so that the resulting walk is stable. Stability is assured by calculating zero momentum point with largest stability margin in Matlabs.

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DEMN

https://doi.org/10.1007/978-94-017-6561-9than evaluating fitnesses solely with built-in compiler routines. Using a stochastic optimizer on real-world problems can be quite challenging because every run returns a different “best” fitness. This issue is addressed by making many runs, often hundreds, possibly even thousands, in order to gener

exostosis

https://doi.org/10.1007/978-94-017-6561-9simplicity and complexity. The former feature is to allow analysing the behaviour of algorithms, whereas the latter is to mimic real-world problems. Despite the importance of the test functions, however, there are currently neither empirical studies on the suitability of the existing test functions

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https://doi.org/10.1007/978-90-313-7582-0 non-deterministic optimization algorithms. In this article, the convergence of gravitational search algorithm (GSA) is discussed over linear and quadratic functions. A theoretical proof of convergence for GSA is provided for linear and quadratic functions. The article ensures the convergence of GSA

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B. Willemse,E. J. Duiverman,K. Knol algorithms, and programs) based on the given experimental data, sets of variables, basic functions, and operations. The proposed algorithm of multivariant evolutionary synthesis of nonlinear models includes a linear representation of a chromosome by real variables, simple operations in decoding of

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