Tuomo Rossi

Bio: Tuomo Rossi is an academic researcher from Information Technology University. The author has contributed to research in topics: Boundary value problem & Finite element method. The author has an hindex of 17, co-authored 62 publications receiving 994 citations. Previous affiliations of Tuomo Rossi include University of Jyväskylä.

An enhanced memetic differential evolution in filter design for defect detection in paper production

Abstract: This article proposes an Enhanced Memetic Differential Evolution (EMDE) for designing digital filters which aim at detecting defects of the paper produced during an industrial process. Defect detection is handled by means of two Gabor filters and their design is performed by the EMDE. The EMDE is a novel adaptive evolutionary algorithm which combines the powerful explorative features of Differential Evolution with the exploitative features of three local search algorithms employing different pivot rules and neighborhood generating functions. These local search algorithms are the Hooke Jeeves Algorithm, a Stochastic Local Search, and Simulated Annealing. The local search algorithms are adaptively coordinated by means of a control parameter that measures fitness distribution among individuals of the population and a novel probabilistic scheme. Numerical results confirm that Differential Evolution is an efficient evolutionary framework for the image processing problem under investigation and show that the EMDE performs well. As a matter of fact, the application of the EMDE leads to a design of an efficiently tailored filter. A comparison with various popular metaheuristics proves the effectiveness of the EMDE in terms of convergence speed, stagnation prevention, and capability in detecting solutions having high performance.

A Parallel Fast Direct Solver for Block Tridiagonal Systems with Separable Matrices of Arbitrary Dimension

Abstract: A parallel fast direct solution method for linear systems with separable block tridiagonal matrices is considered Such systems appear, for example, when discretizing the Poisson equation in a rectangular domain using the five-point finite difference scheme or the piecewise linear finite elements on a triangulated, possibly nonuniform rectangular mesh The method under consideration has the arithmetical complexity ${\mathcal O}(N\log N)$, and it is closely related to the cyclic reduction method, but instead of using the matrix polynomial factorization, the so-called partial solution technique is employed Hence, in this paper, the method is called the partial solution variant of the cyclic reduction method (PSCR method) The method is presented and analyzed in a general radix-q framework and, based on this analysis, the radix-4 variant is chosen for parallel implementation using the MPI standard The generalization of the method to the case of arbitrary block dimension is described The numerical experiments show the sequential efficiency and numerical stability of the PSCR method compared to the well-known BLKTRI implementation of the generalized cyclic reduction method The good scalability properties of the parallel PSCR method are demonstrated in a distributed-memory Cray T3E-750 computer

Comparison of implementations of the lattice-Boltzmann method

Abstract: Simplicity of coding is usually an appealing feature of the lattice-Boltzmann method (LBM). Conventional implementations of LBM are often based on the two-lattice or the two-step algorithm, which however suffer from high memory consumption and poor computational performance, respectively. The aim of this work was to identify implementations of LBM that would achieve high computational performance with low memory consumption. Effects of memory addressing schemes were investigated in particular. Data layouts for velocity distribution values were also considered, and they were found to be related to computational performance. A novel bundle data layout was therefore introduced. Addressing schemes and data layouts were implemented for the Lagrangian, compressed-grid (shift), swap, two-lattice, and two-step algorithms. Implementations were compared for a wide range of fluid volume fractions. Simulation results indicated that indirect addressing implementations yield high computational performance. However, they achieved low memory consumption only for very low fluid volume fractions. Semi-direct addressing implementations could also provide high computational performance. The bundle data layout was found to be competitive, sometimes by a wide margin, in all the cases considered.

Fitness diversity based adaptation in Multimeme Algorithms:A comparative study

Abstract: This paper compares three different fitness diversity adaptations in multimeme algorithms (MmAs). These diversity indexes have been integrated within a MmA present in literature, namely fast adaptive memetic algorithm. Numerical results show that it is not possible to establish a superiority of one of these adaptive schemes over the others and choice of a proper adaptation must be made by considering features of the problem under study. More specifically, one of these adaptations outperforms the others in the presence of plateaus or limited range of variability in fitness values, another adaptation is more proper for landscapes having distant and strong basins of attraction, the third one, in spite of its mediocre average performance can occasionally lead to excellent results.

Differential Evolution: A Survey of the State-of-the-Art

Abstract: Differential evolution (DE) is arguably one of the most powerful stochastic real-parameter optimization algorithms in current use. DE operates through similar computational steps as employed by a standard evolutionary algorithm (EA). However, unlike traditional EAs, the DE-variants perturb the current-generation population members with the scaled differences of randomly selected and distinct population members. Therefore, no separate probability distribution has to be used for generating the offspring. Since its inception in 1995, DE has drawn the attention of many researchers all over the world resulting in a lot of variants of the basic algorithm with improved performance. This paper presents a detailed review of the basic concepts of DE and a survey of its major variants, its application to multiobjective, constrained, large scale, and uncertain optimization problems, and the theoretical studies conducted on DE so far. Also, it provides an overview of the significant engineering applications that have benefited from the powerful nature of DE.

A new version of detached-eddy simulation, resistant to ambiguous grid densities

Abstract: Detached-eddy simulation (DES) is well understood in thin boundary layers, with the turbulence model in its Reynolds-averaged Navier–Stokes (RANS) mode and flattened grid cells, and in regions of massive separation, with the turbulence model in its large-eddy simulation (LES) mode and grid cells close to isotropic. However its initial formulation, denoted DES97 from here on, can exhibit an incorrect behavior in thick boundary layers and shallow separation regions. This behavior begins when the grid spacing parallel to the wall Δ∥ becomes less than the boundary-layer thickness δ, either through grid refinement or boundary-layer thickening. The grid spacing is then fine enough for the DES length scale to follow the LES branch (and therefore lower the eddy viscosity below the RANS level), but resolved Reynolds stresses deriving from velocity fluctuations (“LES content”) have not replaced the modeled Reynolds stresses. LES content may be lacking because the resolution is not fine enough to fully support it, and/or because of delays in its generation by instabilities. The depleted stresses reduce the skin friction, which can lead to premature separation.

Detached-Eddy Simulation

Abstract: Detached-eddy simulation (DES) was first proposed in 1997 and first used in 1999, so its full history can be surveyed. A DES community has formed, with adepts and critics, as well as new branches. The initial motivation of high–Reynolds number, massively separated flows remains, for which DES is convincingly more capable presently than either unsteady Reynolds-averaged Navier-Stokes (RANS) or large-eddy simulation (LES). This review discusses compelling examples, noting the visual and quantitative success of DES. Its principal weakness is its response to ambiguous grids, in which the wall-parallel grid spacing is of the order of the boundary-layer thickness. In some situations, DES on a given grid is then less accurate than RANS on the same grid or DES on a coarser grid. Partial remedies have been found, yet dealing with thickening boundary layers and shallow separation bubbles is a central challenge. The nonmonotonic response of DES to grid refinement is disturbing to most observers, as is the absence of...

Hyper-heuristics: a survey of the state of the art

Abstract: Hyper-heuristics comprise a set of approaches that are motivated (at least in part) by the goal of automating the design of heuristic methods to solve hard computational search problems. An underlying strategic research challenge is to develop more generally applicable search methodologies. The term hyper-heuristic is relatively new; it was first used in 2000 to describe heuristics to choose heuristics in the context of combinatorial optimisation. However, the idea of automating the design of heuristics is not new; it can be traced back to the 1960s. The definition of hyper-heuristics has been recently extended to refer to a search method or learning mechanism for selecting or generating heuristics to solve computational search problems. Two main hyper-heuristic categories can be considered: heuristic selection and heuristic generation. The distinguishing feature of hyper-heuristics is that they operate on a search space of heuristics (or heuristic components) rather than directly on the search space of solutions to the underlying problem that is being addressed. This paper presents a critical discussion of the scientific literature on hyper-heuristics including their origin and intellectual roots, a detailed account of the main types of approaches, and an overview of some related areas. Current research trends and directions for future research are also discussed.