Efficient hybrid methods for global continuous optimization based on simulated annealing

Miettinen, Kaisa; Mäkelä, Marko M.; Maaranen, Heikki

doi:10.1016/j.cor.2004.09.005

Cited by 19 publications

(18 citation statements)

References 37 publications

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“…To decrease the computational cost, the diversification phase can stop earlier in order to start the intensification phase. However, the switching time between the diversification and the intensification is very important [37]. A very early switch to the intensification, increases the possibility of trapping in local minima.…”

Section: Hybrid Approachesmentioning

confidence: 99%

“…The most common meta-heuristic approaches which have been used in GCO are TS [3,5,9,24,20,21,29,32,36,42,51], GA [4,26,47], PSO [1,15,26,41,50], SA [37], artificial bee colony [27], artificial immune systems [11] and ACO [12][13][14]44,46]. For the intensification, different approaches like NM [4,5,15,20,26], proximal bundle method [37], APS [19,20], Hooke-Jeeves direct search method [23] and ACO [41] have been applied.…”

Section: Hybrid Approachesmentioning

confidence: 99%

“…Also most of the time they can avoid the traps of local minima [37]. Among all meta-heuristics, tabu search (TS) stresses emphasis on escaping from local minima by introducing the concept of a list.…”

Section: Introductionmentioning

confidence: 99%

“…Other meta-heuristic approaches like Simulated Annealing (SA) [37], Ant Colony Optimization (ACO) [12,41,44], Genetic Algorithms (GA) [4,28,47], Particle Swarm Optimization (PSO) [26,28,41,49,50] and harmony search [30,33] have been applied in GCO. As mentioned earlier, meta-heuristic methods are mostly hybridized with LOMs to increase the speed of convergence.…”

Section: Introductionmentioning

confidence: 99%

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Hybrid optimization with improved tabu search

Mashinchi¹,

Orgun²,

Pedrycz³

2011

Applied Soft Computing

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Section: Hybrid Approachesmentioning

confidence: 99%

Section: Hybrid Approachesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Hybrid optimization with improved tabu search

Mashinchi¹,

Orgun²,

Pedrycz³

2011

Applied Soft Computing

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“…In the case of genetic algorithms, continuous variables can be converted into binary ones after which normal genetic algorithm procedures can be used (Chelouah and Siarry 2000). Moreover, hybridation of heuristics has been also employed as a method to deal with continuous variables (Wikström and Eriksson 2000, Chelouah and Siarry 2005, Miettinen et al 2006.…”

Section: Heuristics and Meta Modelsmentioning

confidence: 99%

Optimising forest stand management in Galicia, north-western Spain

Pasalodos-Tato¹

2010

Diss. For.

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The present thesis aims at developing instructions for the optimal management of pine stands in Galicia in order to maximise the economic profitability of these stands. Galicia is a Spanish region characterised by the high productivity of its forests, Pinus pinaster, Pinus radiata and Pinus sylvestris being Galicia's most important conifers. Analytical methods have not been effectively applied in Galician forest management. The main objective of the present thesis was to develop management tools that ease the management in Galician pine stands, thus enhancing the profitability of forestry. Employing stand growth and yield models in combination with an optimisation algorithm, models for the optimal management of pine stands were developed. Since optimal management is sensitive to market conditions, timber price and discounting rate were used as predictors in the models (studies I-III) in addition to other predictors such as site index and planting density. The main challenge for the development of Galician pine stands is the constant presence of forest fires that complicate both management and economic analyses. High risk of fire makes it necessary to include fire risk considerations in the analyses when developing instructions for the optimal management. Fire risk was characterised and analysed as an exogenous (study II) or endogenous (studies III-IV) factor, observing that the manner in which fire risk is characterised affects the conclusions about optimal forest management. Another novelty of this thesis was the analysis of silvopastoral systems as an alternative to mere timberoriented schedules under conditions of high fire risk (study IV). The results (studies I-IV) showed that optimal management was highly sensitive to market and fire risk conditions, an increase in both discounting rate and fire risk shortening rotation optimal lengths. The models for optimal management developed in the thesis allow great flexibility for adapting the instructions to every possible economic and risk situation. Study IV showed that grazing in the forest improved profitability.

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