线性规划、模拟退火和遗传算法在杉木人工林可持续经营中的应用和比较

doi:10.11707/j.1001-7488.20040314

Scientia Silvae Sinicae ›› 2004, Vol. 40 ›› Issue (3): 80-87.doi: 10.11707/j.1001-7488.20040314

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The Application and Comparison of Linear Programming, Simulated Annealing and Genetic Algorithm in the Sustainable Management of Cunninghamia lanceolata Plantations

Chen Bowang,Hui Gangying,Klaus von Gadow

Research Institute of Forestry,CAF Beijing100091；Institute of Forest Resource Management, Georg-August-University Gttingen37075

Received:2001-04-08 Revised:1900-01-01 Online:2004-05-25 Published:2004-05-25

Abstract

Abstract:

The methods of Simulated Annealing and Genetic Algorithm were introduced by using an example of Cunninghamia lanceolata plantation. Their application in sustainable forest management was compared with Linear Programming by the common model and the same data set. Basic growth and yield information were provided using a model developed by Hui (1997). Linear Programming will establish an optimal solution if it exists, but stand splitting cannot be avoided. Simulated Annealing and Genetic Algorithm converge to an optimum (or near-optimum) resulting in an integer solution, but the proper parameter setting is crucial. If stand splitting is allowed, and the constraints are sufficiently tight, the Linear Programming solution can be expected to be better than that of Simulated Annealing and Genetic Algorithm.

Key words: Cunninghamia lanceolata, Linear Programming, Simulated Annealing, Genetic Algorithm, Sustainable management

Chen Bowang;Hui Gangying;Klaus von Gadow. The Application and Comparison of Linear Programming, Simulated Annealing and Genetic Algorithm in the Sustainable Management of Cunninghamia lanceolata Plantations[J]. Scientia Silvae Sinicae, 2004, 40(3): 80-87.

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The Application and Comparison of Linear Programming, Simulated Annealing and Genetic Algorithm in the Sustainable Management of Cunninghamia lanceolata Plantations

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