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Articles containing the keyword 'goal programming'

Category: Article

article id 5484, category Article
Jyrki Kangas, Timo Pukkala. (1992). A decision theoretic approach applied to goal programming of forest management. Silva Fennica vol. 26 no. 3 article id 5484. https://doi.org/10.14214/sf.a15645
Keywords: forest management; models; forest planning; decision analysis; goal programming; optimization methods
Abstract | View details | Full text in PDF | Author Info

An alternative approach to formulating a forestry goal programming problem is presented. First, single objective optima levels are solved. The Analytical Hierarchy Process is applied in the estimation of a priori weights of deviations from the goal target levels. The ratios of the weights can be interpreted as relative importance of the goals, respectively. The sum of the weighted deviations from all single optima levels associated with the management goals is minimized. Instead of absolute deviations, relative ones are used. A case study problem of forest management planning with several objectives, measured in different units, is analysed.

The PDF includes an abstract in Finnish.

  • Kangas, E-mail: jk@mm.unknown (email)
  • Pukkala, E-mail: tp@mm.unknown

Category: Article

article id 7630, category Article
Esko Mikkonen. (1983). Eräiden matemaattisen ohjelmoinnin menetelmien käyttö puun korjuun ja kuljetuksen sekä tehdaskäsittelyn menetelmävalinnan apuvälineenä. Silva Fennica vol. 0 no. 183 article id 7630. https://doi.org/10.14214/aff.7630
English title: The usefulness of some techniques of the mathematical programming as a tool for the choice of timber harvesting system.
Original keywords: matemaattinen ohjelmointi; standardi lineaarinen optimointi; parametrinen optimointi; tavoiteoptimointi; sekalukuoptimointi; kokonaislukuoptimointi; puunhankinnan suunnittelu
English keywords: mixed integer programming; integer programming; goal programming; wood procurement; mathematical programming; standard linear programming; parametric programming
Abstract | View details | Full text in PDF | Author Info

The applicability of five mathematical programming methods, namely standard linear programming, parametric programming, goal programming, mixed integer programming and integer programming is discussed as a planning tool for the choice of wood procurement method.

Theoretically, the goal programming approach seems to be the best routine for mathematical handling of problems related to wood procurement. The parametric approach must include enough large post-optimality analysis routine. If the effect of the variables expressed with different measures is to be studied, interpretation of the economic information given by the approach becomes a problem. The other drawback is that the approach does not allow determination of the hierarchy of the goals objectively as they depend on the subjective preferences of the decision maker.

From the practical point of view, standard linear programming is the best method if the objective function can be formulated in economic terms, for instance. If there are several goals to be attained or satisfied the best method is goal programming.

According to the sub-studies, every method under consideration can be used as a solution routine for the minimization of wood procurement costs. In cost minimization the best methods are goal programming and standard linear programming. The best method for harvesting system evaluation purposes is parametric because it allows varied cost calculations within a certain cost range. The best method for harvesting equipment investment planning is mixed integer programming with binary decision variables.

The more complicated and restricted the problem environment is, the better the mathematical programming approach will be, also in harvesting related problems.

The PDF includes a summary in English.

  • Mikkonen, E-mail: em@mm.unknown (email)

Category: Research article

article id 1226, category Research article
Santiago Pereira, Antonio Prieto, Rafael Calama, Luis Diaz-Balteiro. (2015). Optimal management in Pinus pinea L. stands combining silvicultural schedules for timber and cone production. Silva Fennica vol. 49 no. 3 article id 1226. https://doi.org/10.14214/sf.1226
Keywords: forest management; goal programming; non-timber forest product
Highlights: Three management scenarios are proposed to integrate timber and pine nuts; Different silvicultural regimes for each output are addressed jointly; Goal programming is used in order to solve forest management models; In the mixed scenario, the area allocated to pine nuts should be notably greater.
Abstract | Full text in HTML | Full text in PDF | Author Info

This work aimed to tackle a timber harvest scheduling problem by simultaneously integrating into the analysis two forestry products derived from the same species: the timber and the pine nut. For this purpose, three management scenarios were proposed: two in which each of the productions is maximised separately, and a third mixed where, in each management unit, the product to which the silvicultural effort should be devoted is decided. After defining a set of objectives, and optimising the rotation length, a multi-criteria model based on goal programming was considered since no feasible solutions have been obtained when employing linear programming. The results in our case study show how the feasible solutions reached can be more attractive for the manager. Specifically, the area to be devoted to timber and cone/pine-nut production was computed in a scenario where the optimal silviculture (oriented towards timber or pine nuts) in each stand was selected, and it was concluded that the area allocated to pine nuts should be notably greater. This situation is the opposite of the current management.

  • Pereira, Technical University of Madrid, ETS Ingenieros de Montes, Ciudad Universitaria s/n, 28040 Madrid, Spain E-mail: spereirasaez@gmail.com
  • Prieto, Technical University of Madrid, ETS Ingenieros de Montes, Ciudad Universitaria s/n, 28040 Madrid, Spain E-mail: antonio.prieto@upm.es
  • Calama, Dpto. Selvicultura y Gestión Forestal, INIA-CIFOR, Ctra. A Coruña km 7.5, 28040 Madrid, Spain E-mail: rcalama@inia.es
  • Diaz-Balteiro, Technical University of Madrid, ETS Ingenieros de Montes, Ciudad Universitaria s/n, 28040 Madrid, Spain E-mail: luis.diaz.balteiro@upm.es (email)
article id 1232, category Research article
Pete Bettinger, Mehmet Demirci, Kevin Boston. (2015). Search reversion within s-metaheuristics: impacts illustrated with a forest planning problem. Silva Fennica vol. 49 no. 2 article id 1232. https://doi.org/10.14214/sf.1232
Keywords: forest planning; heuristics; threshold accepting; tabu search; spatial harvest scheduling; adjacency constraints; mixed integer goal programming
Highlights: The interruption of the sequence of events used to explore a solution space and develop a forest plan, and the re-initiation of the search process from a high-quality, known starting point (reversion) seems necessary for some s-metaheuristics; When using a s-metaheuristic, higher quality forest plans may be developed when the reversion interval is around six iterations of the model.
Abstract | Full text in HTML | Full text in PDF | Author Info
The use of a reversion technique during the search process of s-metaheuristics has received little attention with respect to forest management and planning problems. Reversion involves the interruption of the sequence of events that are used to explore the solution space and the re-initiation of the search process from a high-quality, known starting point. We explored four reversion rates when applied to three different types of s-metaheuristics that have previously shown promise for the forest planning problem explored, threshold accepting, tabu search, and the raindrop method. For two of the s-metaheuristics, we also explored three types of decision choices, a change to the harvest timing of a single management unit (1-opt move), the swapping of two management unit’s harvest timing (2-opt moves), and the swapping of three management unit’s harvest timing (3-opt moves). One hundred independent forest plans were developed for each of the metaheuristic / reversion rate combinations, all beginning with randomly-generated feasible starting solutions. We found that (a) reversion does improve the quality of the solutions generated, and (b) the rate of reversion is an important factor that can affect solution quality.
  • Bettinger, School of Forestry and Natural Resources, 180 E. Green Street, University of Georgia, Athens, Georgia, USA 30602 E-mail: pbettinger@warnell.uga.edu (email)
  • Demirci, General Directorate of Forestry, Ministry of Forest and Water Affairs, Republic of Turkey E-mail: mehmetdemirci@yahoo.com
  • Boston, Department of Forest Engineering, Resources and Management, College of Forestry, Oregon State University, USA E-mail: Kevin.Boston@oregonstate.edu

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