| 1. |
- Kahlert, Maria, et al.
(author)
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Harmonization is more important than experience—results of the first Nordic–Baltic diatom intercalibration exercise 2007 (stream monitoring)
- 2009
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In: Journal of Applied Phycology. - : Springer Science and Business Media LLC. - 0921-8971 .- 1573-5176. ; 21:4, s. 471-482
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Journal article (peer-reviewed)abstract
- The goal of this study was a harmonization of diatom identification and counting among diatomists from the Scandinavian and Baltic countries to improve the comparison of diatom studies in this geographical area. An analysis of the results of 25 diatomists following the European standard EN 14407 during an intercalibration exercise showed that a high similarity was achieved by harmonization and not because of a long experience with diatoms. Sources of error were wrong calibration scales, overlooking of small taxa, especially small Navicula s.l., misidentifications (Eunotia rhomboidea was mistaken for Eunotia incisa) and unclear separation between certain taxa in the identification literature. The latter was discussed during a workshop with focus on the Achnanthes minutissima group, the separation of Fragilaria capucina var. gracilis from F. capucina var. rumpens, and Nitzschia palea var. palea from N. palea var. debilis. The exercise showed also that the Swedish standard diatom method tested here worked fine with acceptable error for the indices IPS (Indice de Polluo-sensibilité Spécifique) and ACID (ACidity Index for Diatoms) when diatomists with a low similarity (Bray–Curtis <60%) with the auditor in at least one of the samples are excluded.
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| 2. |
- Maaranen, Heikki, et al.
(author)
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On initial populations of a genetic algorithm for continuous optimization problems
- 2007
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In: Journal of Global Optimization. - : Springer Science and Business Media LLC. - 0925-5001 .- 1573-2916. ; 37:3, s. 405-436
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Journal article (peer-reviewed)abstract
- Genetic algorithms are commonly used metaheuristics for global optimization, but there has been very little research done on the generation of their initial population. In this paper, we look for an answer to the question whether the initial population plays a role in the performance of genetic algorithms and if so, how it should be generated. We show with a simple example that initial populations may have an effect on the best objective function value found for several generations. Traditionally, initial populations are generated using pseudo random numbers, but there are many alternative ways. We study the properties of different point generators using four main criteria: the uniform coverage and the genetic diversity of the points as well as the speed and the usability of the generator. We use the point generators to generate initial populations for a genetic algorithm and study what effects the uniform coverage and the genetic diversity have on the convergence and on the final objective function values. For our tests, we have selected one pseudo and one quasi random sequence generator and two spatial point processes: simple sequential inhibition process and nonaligned systematic sampling. In numerical experiments, we solve a set of 52 continuous test functions from 16 different function families, and analyze and discuss the results.
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| 3. |
- Miettinen, Kaisa, 1965-, et al.
(author)
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Efficient hybrid methods for global continuous optimization based on simulated annealing
- 2006
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In: Computers & Operations Research. - : Elsevier BV. - 0305-0548 .- 1873-765X. ; 33:4, s. 1102-1116
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Journal article (peer-reviewed)abstract
- We introduce several hybrid methods for global continuous optimization. They combine simulated annealing and a local proximal bundle method. Traditionally, the simplest hybrid of a global and a local solver is to call the local solver after the global one, but this does not necessarily produce good results. Besides, using efficient gradient-based local solvers implies that the hybrid can only be applied to differentiable problems. We show several ways how to integrate the local solver as a genuine part of simulated annealing to enable both efficient and reliable solution processes. When using the proximal bundle method as a local solver, it is possible to solve even nondifferentiable problems. The numerical tests show that the hybridization can improve both the efficiency and the reliability of simulated annealing.
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