Consider the problem of determining whether or not a partial dissimilarity matrix can be completed to a Euclidean distance matrix. The dimension of the distance matrix may be restricted and the known dissimilarities may be permitted to vary subject to bound constraints. This problem can be formulated as an optimization problem for which the global minimum is zero if and only if completion is po...

Population-based search algorithms (PBSAs), including swarm intelligence algorithms (SIAs) and evolutionary algorithms (EAs), are competitive alternatives for solving complex optimization problems and they have been widely applied to real-world optimization problems in different fields. In this study, a novel population-based across neighbourhood search (ANS) is proposed for numerical optimizat...

In this paper, a normalized oating point representation has been used for making it be possible to design biotechnical genetic operators as well as to apply some genetic operators like inversion. To improve the adaptation of evolutionary algorithms and avoid the biases which may exist in some genetic operators, we have designed and applied several kinds of genetic operators with some probabilit...

In this paper, we present ReaS, a technique that combines numerical optimization with SAT solving to synthesize unknowns in a program that involves discrete and floatingpoint computation. ReaS makes the program end-to-end differentiable by smoothing any Boolean expression that introduces discontinuity such as conditionals and relaxing the Boolean unknowns so that numerical optimization can be p...

In this paper, monkey algorithm (MA) is designed to solve global numerical optimization problems with continuous variables. The algorithm mainly consists of climb process, watch-jump process, and somersault process in which the climb process is employed to search the local optimal solution, the watch-jump process to look for other points whose objective values exceed those of the current soluti...

We discuss a general approach to hybridize traditional construction heuristics for combinatorial optimization problems with numerical based evolutionary algorithms. Therefore, we show how to augment a construction heuristic with real-valued parameters, called control values. An evolutionary algorithm for numerical optimization uses this enhanced heuristic to find assignments for these control v...

This paper is concerned with the identification of the geometric structure of the boundary for a two-dimensional (stationary) elliptic equation. The domain identification problem is considered as a variational problem to minimize a defect functional, which utilizes some additional data on certain (known) parts of the boundary. The Gradient Projection Method is introduced for this problem and nu...

NUMERICAL OPTIMIZATION FOR TRANSPORT AND REGISTRATION PROBLEMS By Raya Horesh In this thesis we develop numerical methods for the solution of largescale PDE-based constrained optimization problems. Overall three studies are presented; the first two are application driven, addressing volume preserving image registration and optimal mass transport problems. The third study is more generic and emb...

10 to a distance matrix|if a completion does exist, then typically we want to nd it. Although the numerical optimization approach is not deenitive in the sense of Johnson and Tarazaga 8], it is constructive in the sense that it produces a sequence of dissimilarity matrices that converges to a completion. Beyond its ability to construct (approximate) completions, the compelling advantage of the ...

This paper presents search methods to optimize word-length for digital systems. Finding the word-length is tedious work when the variables for optimization are numerous. We have proposed sequential and preplanned searches to find out optimum wordlength, and compared them in terms of the trials. A comparison for a given optimized point is evaluated. We apply them to word-length optimization for ...