Advertisement

Multiple Criteria Decision-Making in Forest Planning: Recent Results and Current Challenges

  • Luis Diaz-Balteiro
  • Carlos Romero
Part of the International Series In Operations Research amp; Mana book series (ISOR, volume 99)

Forest management is becoming a complex process that requires decision making involving economic, environmental and social criteria. This means that multiple criteria decision-making (MCDM) approaches need to be used in many forestry contexts. This chapter aims at assessing the efforts undertaken over the last 30 years towards formulating and solving forest management problems from an MCDM perspective. The goal of the chapter is not to compile an exhaustive list of MCDM applications in forestry but to detect the areas within forest management in which MCDM approaches have proven to be more productive or have significant future potential.

Keywords

Forest Management Goal Programming Forest Planning Goal Programming Model Goal Programming Approach 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bantayan, N. C., and Bishop, I. D., 1998, Linking objective and subjective modelling for landuse decision-making. Landscape and Urban Planning 43: 35-48.CrossRefGoogle Scholar
  2. Bell, D. E., 1977, A decision analysis of objectives for a forest pest problem, in: Conflicting Objectives in Decisions, D. D. Bell, R. L. Keeney, and H. E. Raiffa, ed., Wiley, New York, pp. 389-418.Google Scholar
  3. Bertier, P., and Montgolfier, J., 1974, On multicriteria analysis: an application to a forest management problem. Metra 13: 33-45.Google Scholar
  4. Bertomeu, M., and Romero, C., 2001, Managing forest biodiversity: a zero-one goal programming approach. Agricultural Systems 68: 197-213.CrossRefGoogle Scholar
  5. Bertomeu, M., and Romero, C., 2002, Forest management optimisation models and habitat diversity: a goal programming approach. Journal of the Operational Research Society 53: 1175-1184.CrossRefGoogle Scholar
  6. Bevers, M., and Hof, J., 1999, Spatially optimizing wildlife habitat edge effects in forest management linear and mixed-integer programs. Forest Science 45: 249-258.Google Scholar
  7. Bojórquez-Tapia, L. A., De La Cueva, H., Díaz, S., Melgarejo, D., Alcantar, G., Solares, M. J., Grobet, G., and Cruz-Bello, G., 2004, Environmental conflicts and nature reserves: redesigning Sierra San Pedro Mártir National Park, Mexico. Biological Conservation 117: 111-126.CrossRefGoogle Scholar
  8. Bousson, E., 2001, Development of a multicriteria decision support system adapted to multiple-use forest management: application to forest management at the management unit level in Southern Belgium, in: Criteria and Indicators for Sustainable Forest Management at the Forest Management Unit Level, A. Franc, O. Laroussinie, and T. Karjalainen, eds., EFI Proceedings, Joensuu, Finland, pp. 151-164.Google Scholar
  9. Buongiorno, J., Dahir, S., Chih Lu, H., and Ching-Rong, L., 1994, Tree size diversity and economic returns in uneven-aged forest stands. Forest Science 40: 83-103.Google Scholar
  10. Buongiorno, J., Peyron, J. L., Houllier, F., and Bruciamacchie, M., 1995, Growth and management of mixed-species, uneven-aged forests in the French Jura: implications for economic returns and tree diversity. Forest Science 41: 397-429.Google Scholar
  11. Carter, D. R., Vogiatzis, M., Moss, C. B., and Arvanitis, L. G., 1997, Ecosystem management or infeasible guidelines? Implications of adjacency constraints for wildlife habitat and timber production. Canadian Journal of Forest Research 27: 1302-1310.Google Scholar
  12. Chang, S., and Buongiorno, J., 1981, A programming for multiple use forestry. Journal of Environmental Management 13: 45-58.Google Scholar
  13. Charnes, A., and Cooper, W. W., 1961, Management Models and Industrial Applications of Linear Programming, John Wiley and Sons, New York.Google Scholar
  14. Cohon, J. L., 1978, Multiobjective Programming and Planning, Academic Press, New York.Google Scholar
  15. Diaz-Balteiro, L., and Romero, C., 1998, Modeling timber harvest scheduling problems with multiple criteria: an application in Spain. Forest Science 44: 47-57.Google Scholar
  16. Diaz-Balteiro, L., and Romero, C., 2003, Forest management optimisation models when carbon captured is considered: a goal programming approach. Forest Ecology and Management 174: 447-457.CrossRefGoogle Scholar
  17. Diaz-Balteiro, L., and Romero, C., 2004, Sustainability of forest management plans: a discrete goal programming approach. Journal of Environmental Management 71: 351-359.CrossRefGoogle Scholar
  18. Diaz-Balteiro, L., and Romero, C., 2004, MCDM and forest management: a review. Working Paper, Technical University of Madrid.Google Scholar
  19. Ducey, M. J., and Larson, B. C., 1999, A fuzzy set approach to the problem of sustainability. Forest Ecology and Management 115: 29-40.CrossRefGoogle Scholar
  20. Field, D. B., 1973, Goal programming for forest management. Forest Science 19: 125-135.Google Scholar
  21. Field, R. C., Dress, P. E., and Fortson, J. C., 1980, Complementary linear and goal programming procedures for timber harvest scheduling. Forest Science 26: 121-133.Google Scholar
  22. Forman, E. H., and Gass, S. I., 2001, The analytic hierarchy process-an exposition. Operations Research 49: 469-486.CrossRefGoogle Scholar
  23. Fraser, N. M., and Hauge, J. W., 1998, Multicriteria approval: application of approval voting concepts to MCDM problems. Journal of Multi-Criteria Decision Analysis 7: 263-272.CrossRefGoogle Scholar
  24. Hotvedt, J. E., 1983, Application of linear goal programming to forest harvest scheduling. Southern Journal Agricultural Economics 15: 103-108.Google Scholar
  25. Hotvedt, J. E., Leuschner, W. A., and Buhyoff, G. J., 1982, A heuristic weight determination procedure for goal programs used for harvest scheduling models. Canadian Journal of Forest Research 12: 292-298.CrossRefGoogle Scholar
  26. Ignizio, J. P., 1976, Goal Programming and Extensions, Lexington Books, Lexington, MA.Google Scholar
  27. Ignizio, J. P., and Romero, C., 2003, Goal programming, in: Encyclopedia of Information Systems, Vol. 2, H. Bidgoli, ed., Academic Press, San Diego, CA, pp. 489-500.Google Scholar
  28. Kangas, J., Alho, J. M., Kolehmainen, O., and Mononen, A., 1998, Analyzing consistency of experts’ judgements-case of assessing forest biodiversity. Forest Science 44: 610-617.Google Scholar
  29. Kangas, J., and Kangas, A., 2002, Multiple criteria decision support methods in forest management: an overview and comparative analyses, in: Multi-Objective Forest Planning, E. T. Pukkala, ed., Kluwer Academic Publishers, pp. 37-70.Google Scholar
  30. Kangas, J., and Kangas, A., 2003, Multicriteria approval and Smaa-O in natural resources decision analysis with both ordinal and cardinal criteria. Journal of Multi-Criteria Decision Analysis 12: 3-15.CrossRefGoogle Scholar
  31. Kangas, J., and Kuusipalo, J., 1993, Integrating biodiversity into forest management planning and decision-making. Forest Ecology and Management 61: 1-15.CrossRefGoogle Scholar
  32. Kangas, J., and Pukkala, T., 1996, Operationalization of biodiversity as a decision objective in tactical forest planning. Canadian Journal of Forest Research 26: 103-111.CrossRefGoogle Scholar
  33. Kao, C., and Brodie, J. D., 1979, Goal programming for reconciling economic, even flow, and regulation objectives in forest harvest scheduling. Canadian Journal of Forest Research 9: 525-531.Google Scholar
  34. Keeney, R. L., and Raiffa, H., 1976, Decision with Multiple Objectives: Preferences and Value Trade-Offs, John Wiley and Sons, New York.Google Scholar
  35. Kuusipalo, J., and Kangas, J., 1994, Managing biodiversity in a forest environment. Conservation Biology 8: 450-460.CrossRefGoogle Scholar
  36. Laukkanen, S., Kangas, A., and Kangas, J., 2002, Applying voting theory in natural resource management: a case of multiple-criteria group decision support. Journal of Environmental Management 64: 127-137.CrossRefGoogle Scholar
  37. Laukkanen, S., Palander, T., and Kangas, J., 2004, Applying voting theory in participatory decision support for sustainable timber harvesting. Canadian Journal of Forest Research 34: 1511-1524.CrossRefGoogle Scholar
  38. Mendoza, G. A., and Prabhu, R., 2001, A fuzzy analytic hierarchy process for assessing biodiversity conservation, in: The Analytic Hierarchy Process in Natural Resource and Environmental Decision Making., D. L. Schmoldt, J. Kangas, G. A. Mendoza, and M. Pesonen, ed., Kluwer Academic Publishers, Dordrecht, pp. 219-233.Google Scholar
  39. Mendoza, G. A., and Prabhu, R., 2000, Multiple criteria decision making approaches to assessing forest sustainability using criteria and indicators: a case study. Forest Ecology and Management 131: 107-126.CrossRefGoogle Scholar
  40. Mendoza, G. A., and Prabhu, R., 2003, Qualitative multi-criteria approaches to assessing indicators of sustainable forest resource management. Forest Ecology and Management 174: 329-343.CrossRefGoogle Scholar
  41. Mendoza, G. A., and Sprouse, W., 1989, Forest planning and decision making under fuzzy environments: an overview and illustration. Forest Science 35: 481-502.Google Scholar
  42. Mendoza, G. A., Hartanto, H., Prabhu, R., and Villanueva, T., 2002, Multicriteria and critical threshold value analysis in assessing sustainable forestry: model development and application. Journal of Sustainable Forestry 15: 25-62.CrossRefGoogle Scholar
  43. Önal, H., 1997, Trade-off between structural diversity and economic objectives in forest management diversity. American Journal of Agricultural Economics 79: 1001-1012.CrossRefGoogle Scholar
  44. Önal, H., 1997, A computationally convenient diversity measure: theory and application. Environmental and Resource Economics 9: 409-427.Google Scholar
  45. Phua, M., and Minowa, M., 2004, A GIS-based multi-criteria decision making approach to forest conservation planning at a landscape scale: a case study in the Kinabalu Area, Sabah, Malaysia. Landscape and Urban Planning, 71: 207-222.CrossRefGoogle Scholar
  46. Pukkala, T., and Kangas, J., 1993, A heuristic optimisation method for forest planning and decision-making. Scandinavian Journal of Forest Research 8: 560-570.CrossRefGoogle Scholar
  47. Pykalainen, J., Pukkala, T., and Kangas, J., 2001, Alternative priority models for forest planning on the landscape level involving multiple ownership. Forest Policy and Economics 2: 293-306.CrossRefGoogle Scholar
  48. Riitters, K., Brodie, J. D., and Kao, C., 1982, Volume versus value maximization illustrated for Douglas-fir with thinning. Journal of Forestry 80: 83-89, 107.Google Scholar
  49. Romero, C., 2001, Extended lexicographic goal programming: a unifying approach. Omega. The International Journal of Management Science 29: 63-71.CrossRefGoogle Scholar
  50. Romero, C., 2004, A general structure of achievement function for a goal programming model. European Journal of Operational Research 153: 675-686.CrossRefGoogle Scholar
  51. Roy, B., 1968, Classement Et Choix En Presence De Points De Vue Multiples (La Methode ELECTRE). Revue Francaise d’Informatique et de Recherche Operationnelle 8: 57-75.Google Scholar
  52. Roy, B., 1991, The outranking approach and the foundations of ELECTRE methods. Theory and Decision 31: 49-73.CrossRefGoogle Scholar
  53. Saaty, T. L., 1977, A scaling method for priorities in hierachical structures. Journal of Mathematical Psychology 15: 234-281.CrossRefGoogle Scholar
  54. Saaty, T. L., 1980, The Analytic Hierachy Process: Planning, Priority Setting, and Resource Allocation, McGraw-Hill, New York.Google Scholar
  55. Schmoldt, D. L., and Peterson, D. L., 2000, Analytical group decision making in natural resources: methodology and application. Forest Science 46: 62-75.Google Scholar
  56. Schmoldt, D. L., and Peterson, D. L., 2001, Efficient group decision making in workshop settings, in: The Analytic Hierarchy Process in Natural Resource and Environmental Decision Making, D. L. Schmoldt, J. Kangas, G. A. Mendoza, and M. Pesonen, ed., Kluwer Academic Publishers, Dordrecht, pp. 97-114.Google Scholar
  57. Shields, D. J., Tolwinski, B., and Kent, B. M., 1999, Models for conflict resolution in ecosystem management. Socio-Economic Planning Sciences 33: 61-84.CrossRefGoogle Scholar
  58. Snyder, S., and Revelle, C., 1997, Multiobjective grid packing model: an application in forest management. Location Science 5: 165-180.CrossRefGoogle Scholar
  59. Steuer, R. E., 1989, Multiple Criteria Optimization: Theory, Computation and Application, John Wiley and Sons, New York.Google Scholar
  60. Tarp, P., and Helles, F., 1995, Multi-criteria decision-making in forest management planning - an overview. Journal of Forest Economics 1: 273-306.Google Scholar
  61. Tecle, A., Shrestha, B. P., and Duckstein, L., 1998, A multiobjective decision support system for multiresource forest management. Group Decision and Negotiation 7: 23-40.CrossRefGoogle Scholar
  62. USDA Forest Service, 1997, Spectrum Users Guide, Ecosystem Management Analysis Center, Fort Collins, CO.Google Scholar
  63. Yu, P. L., 1973, A class of solutions for group decision problems. Management Science 19: 936-946.CrossRefGoogle Scholar
  64. Zeleny, M., 1974, A concept of compromise solutions and the method of the displaced ideal. Computers & Operations Research 1: 479-496.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2007

Authors and Affiliations

  • Luis Diaz-Balteiro
    • 1
  • Carlos Romero
    • 1
  1. 1.Department of Forest Economics and ManagementTechnical University of MadridSpain

Personalised recommendations