1. |
- Haarala, M, et al.
(author)
-
New limited memory bundle method for large-scale nonsmooth optimization
- 2004
-
In: Optimization Methods and Software. - : Informa UK Limited. - 1055-6788 .- 1029-4937. ; 19:6, s. 673-692
-
Journal article (peer-reviewed)abstract
- Many practical optimization problems involve nonsmooth (that is, not necessarily differentiable) functions of hundreds or thousands of variables. In such problems, the direct application of smooth gradient-based methods may lead to a failure due to the nonsmooth nature of the problem. On the other hand, none of the current general nonsmooth optimization methods is efficient in large-scale settings. In this article, we describe a new limited memory variable metric based bundle method for nonsmooth large-scale optimization. In addition, we introduce a new set of academic test problems for large-scale nonsmooth minimization. Finally, we give some encouraging results from numerical experiments using both academic and practical test problems.
|
|
2. |
- Hakanen, Jussi, et al.
(author)
-
An Application of Multiobjective Optimization to Process Simulation
- 2004
-
In: CD-Proceedings of 4th European Congress on Computational Methods in Applied Sciences and Engineering.
-
Conference paper (peer-reviewed)abstract
- We study multiobjective optimization problems arising from chemical process simulation. Interactive multiobjective optimization method NIMBUS, developed at the University of Jyväskylä, is combined with the BALAS process simulator, developed at theTechnical Research Center of Finland, in order to provide a new interactive tool for designing chemical processes. Continuous interaction between the method and the designer provides an efficient approach to explore the Pareto optimal solutions and helps the designer to learn about the behaviour of the process. This new approach has been applied to a water allocation problem for an integrated plant containing a thermomechanical pulping plant and a paper mill.
|
|
3. |
- Hämäläinen, Jari, et al.
(author)
-
Multiobjective Decision Making for Papermaking
- 2004
-
In: CD-Proceedings of MCDM2004, the 17th International Conference on Multiple Criteria Decision Making.
-
Conference paper (other academic/artistic)
|
|
4. |
- Kaitala, A, et al.
(author)
-
Is nonparental egg carrying parental care?
- 2001
-
In: Behavioral Ecology. - : Oxford University Press (OUP). - 1045-2249 .- 1465-7279. ; 12:3, s. 367-368
-
Journal article (peer-reviewed)
|
|
5. |
|
|
6. |
|
|
7. |
|
|
8. |
|
|
9. |
|
|
10. |
- Maaranen, Heikki, et al.
(author)
-
Quasi-random initial population for genetic algorithms
- 2004
-
In: Computers and Mathematics with Applications. - : Elsevier BV. - 0898-1221 .- 1873-7668. ; 47:12, s. 1885-1895
-
Journal article (peer-reviewed)abstract
- The selection of the initial population in a population-based heuristic optimizationmethod is important, since it affects the search for several iterations and often has an influence on the final solution. If no a priori information about the optima is available, the initial population is often selected randomly using pseudorandom numbers. Usually, however, it is more important that the points are as evenly distributed as possible than that they imitate random points. In this paper, we study the use of quasi-random sequences in the initial population of a genetic algorithm. Sample points in a quasi-random sequence are designed to have good distribution properties. Here a modified genetic algorithm using quasi-random sequences in the initial population is tested by solving a large number of continuous benchmark problems from the literature. The numerical results of two implementations of genetic algorithms using different quasi-random sequences are compared to those of a traditional implementation using pseudorandom numbers. The results obtained are promising.
|
|