On the optimization of unimodal functions with the (1+1) evolutionary algorithm - Droste, Jansen, et al. - 1998 () Citation Context ...roximate optimal rate), and may apply to any linear binary function [43]. Rudolph proves [11] that the algorithm can solve LeadingOnes in O(L 2 ),...
The Integral of a Symmetric Unimodal Function over a Symmetric Convex Set and Some Probability Inequalities Prediction of the Viscosity of Multimodal Suspensions from Unimodal Viscosity Data A Real-Coded Genetic Algorithm for Function Optimization Using the Unimodal Normal Distribution Crossover ...
Under the premise of these principles, we propose a novel loss function for fully adaptive label distribution learning, namely unimodal-concentrated loss. Specifically, the uni- modal loss derived from the learning to rank strategy con- strains the di...
A gradient relaxation method based on maximizing a criterion function is studied and compared to the nonlinear probabilistic relaxation method for the purpose of segmentation of images having unimodal distributions. Although both methods provide comparable segmentation results, the gradient method has the ad...
Moreover, the optimal FOPID gains, the integral, and the derivative orders (λ, µ) are presented in Table 2 using different optimization techniques. Furthermore, Table 3 shows the optimal fitness function using different controllers for the three studied cases. It can be observed that the ...
Suppose we would simply determine a threshold x where the response function exceeds a given value, γ. This can be accomplished by finding the pivot point for γ in linear time. 2.1. L1-isotonic regression: algorithms The importance of Proposition 2.4 and Theorem 2.9 from the algorithmic point...
Pattnaik, PSO based memetic algorithm for unimodal and multimodal function optimization, Swarm Evol. Memetic Comput. 7076 (2011) 127-134. Lecture Notes in Computer Science.Devi S, Jadhav DG, Pattnaik SS. PSO Based Memetic Algorithm for Unimodal and Multimodal Function Optimization. SEMCCO, Part 1...
Multimodal functionParticle swarm optimization (PSO) performs well for small dimensional and less complicated problems but fails to locate global minima for complex multi-minima functions. This paper proposes an improved particle swarm optimization (IPSO) which introduces Gaussian random variables in ...
The problem of determining the optimal cross-sectional area function along an extensible arch so as to minimize the total volume under given external pressure, fixed frequency, and geometrical constraints is investigated by use of the Pontryagin maximum principle. The optimal design of a clamped-...
Metaheuristic optimization methods have started to be used frequently today in the solution of these problems when a mathematical model cannot be created or a solution cannot be produced in an effective time even if it is created. These methods, by their nature, cannot produce effect...