Applying simulated annealing using different methods for the neighborhood search in forest planning problems

Borges, Paulo Sérgio da Silva; Eid, Tron; Bergseng, Even

doi:10.1016/j.ejor.2013.08.039

Cited by 44 publications

(23 citation statements)

References 37 publications

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“…In our study, we firstly used a uniform probability to select the management unit, and then another two uniform probability distributions were applied to select the time period when the management prescription should occur and the management activity to be applied within the selected management unit. However, Borges et al (2014aBorges et al ( , 2014b recently reported that solutions could be significantly improved when introducing bias into the probabilities for management unit and treatment prescription selection process when compared to unbiased probabilities (i.e., the standard version of heuristic). However, the biased probabilities for selecting choices should be dynamic rather than static.…”

Section: Discussionmentioning

confidence: 99%

“…The s-metaheuristics, such as simulated annealing (Metropolis et al 1953;Öhman and Lämås 2003;Borges et al 2014aBorges et al , 2014b and tabu search (Richards and Gunn 2000;Bettinger et al 2007), typically only maintain one solution per iteration of the search process, and often it represents a feasible solution. These heuristics utilize intensification and diversification search strategies to modify the solution in an attempt to locate the global optimum; these processes can further assist in escaping local optima.…”

Section: Introductionmentioning

confidence: 99%

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Evaluating the neighborhood, hybrid and reversion search techniques of a simulated annealing algorithm in solving forest spatial harvest scheduling problems

Dong¹,

Bettinger²,

Liu³

et al. 2016

Silva Fenn.

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Highlights• The performances of neighborhood, hybrid and reversion search strategies of simulated annealing were evaluated when implemented with a forest spatial harvest scheduling problem.• The performances of alternative search strategies of simulated annealing were all systematic and clear better than the conventional strategy.• The reversion techniques were significant superior to the other search strategies in solving forest spatial harvest scheduling problems. AbstractHeuristic techniques have been increasingly used to address the complex forest planning problems over the last few decades. However, heuristics only can provide acceptable solutions to difficult problems, rather than guarantee that the optimal solution will be located. The strategies of neighborhood, hybrid and reversion search processes have been proved to be effective in improving the quality of heuristic results, as suggested recently in the literature. The overall aims of this paper were therefore to systematically evaluate the performances of these enhanced techniques when implemented with a simulated annealing algorithm. Five enhanced techniques were developed using different strategies for generating candidate solutions. These were then compared to the conventional search strategy that employed 1-opt moves (Strategy 1) alone. The five search strategies are classified into three categories: i) neighborhood search techniques that only used the change version of 2-opt moves (Strategy 2); ii) self-hybrid search techniques that oscillate between 1-opt moves and the change version of 2-opt moves (Strategy 3), or the exchange version of 2-opt moves (Strategy 4); iii) reversion search techniques that utilize 1-opt moves and the change version of 2-opt moves (Strategy 5) or the exchange version of 2-opt moves (Strategy 6). We found that the performances of all the enhanced search techniques of simulated annealing were systematic and often clear better than conventional search strategy, however the required computational time was significantly increased. For a minimization planning problem, Strategy 6 produced the lowest mean objective function values, which were less than 1% of the means developed using conventional search strategy. Although Strategy 6 performed very well, the other search strategies should not be neglected because they also have the potential to produce high-quality solutions.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluating the neighborhood, hybrid and reversion search techniques of a simulated annealing algorithm in solving forest spatial harvest scheduling problems

Dong¹,

Bettinger²,

Liu³

et al. 2016

Silva Fenn.

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“…However, different approaches to SA implementation may be more efficient, for example, fast annealing [61] or adaptive annealing [62], or other types of SA such as the great deluge algorithm [63] used by Bettinger et al [60]. At the same time, Borges et al [46] showed that improving the neighborhood search method can enhance the performance of SA for spatial planning. Attempting to decrease the variation in optimal NPVs of SA and enhancing its reliability using all of these methods may be worthwhile.…”

Section: Discussionmentioning

confidence: 99%

“…Lately the performance of SA itself has been analyzed, for example, its sensitivity to the parameters used [45] and its application in neighborhood methods [46]. Thus, SA is commonly used in the field and its performance is evaluated.…”

Section: ∼10mentioning

confidence: 99%

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An Evaluation of the Use of Simulated Annealing to Optimize Thinning Rates for Single Even-Aged Stands

Moriguchi

Ueki

Saito

2015

International Journal of Forestry Research

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We evaluated the potential of simulated annealing as a reliable method for optimizing thinning rates for single even-aged stands. Four types of yield models were used as benchmark models to examine the algorithm's versatility. Thinning rate, which was constrained to 0-50% every 5 years at stand ages of 10-45 years, was optimized to maximize the net present value for one fixed rotation term (50 years). The best parameters for the simulated annealing were chosen from 11 3 patterns, using the mean of the net present value from 39 runs to ensure the best performance. We compared the solutions with those from coarse full enumeration to evaluate the method's reliability and with 39 runs of random search to evaluate its efficiency. In contrast to random search, the best run of simulated annealing for each of the four yield models resulted in a better solution than coarse full enumeration. However, variations in the objective function for two yield models obtained with simulated annealing were significantly larger than those of random search. In conclusion, simulated annealing with optimized parameters is more efficient for optimizing thinning rates than random search. However, it is necessary to execute multiple runs to obtain reliable solutions.

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Constraint Modeling for Forest Management

Eloy

Bushenkov

Abreu

2022

Dynamic Control and Optimization

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Applying simulated annealing using different methods for the neighborhood search in forest planning problems

Cited by 44 publications

References 37 publications

Evaluating the neighborhood, hybrid and reversion search techniques of a simulated annealing algorithm in solving forest spatial harvest scheduling problems

Evaluating the neighborhood, hybrid and reversion search techniques of a simulated annealing algorithm in solving forest spatial harvest scheduling problems

An Evaluation of the Use of Simulated Annealing to Optimize Thinning Rates for Single Even-Aged Stands

Constraint Modeling for Forest Management

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