Abstract
This paper presents preliminary results of research on the development of heuristics for spatially constrained natural resource management problems. These problems encompass constraints on traditional forest product flows over time and constraints on the distribution of harvests over space and time. Emphasis is on designing efficient solution techniques that may take into account the forest-wide temporal and spatial interactions of decisions made on individual stands. Specifically, constraints on minimum and maximum opening sizes and on both the number and size of old growth patches in each planning period are considered. The heuristics are briefly described. Results for an ecosystem management application in Portugal are discussed. Both the quality of the heuristic solutions and computational aspects of implementation are discussed.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Literature Cited
Boston, K. and P. Bettinger. 1999. An Analysis of Monte Carlo Integer Programming, Simulated Annealing, and Tabu Search Heuristics for Solving Spatial Harvest Scheduling Problems. For. Sci. 45:292–301
Covington, W.W., D.B. Wood, D.L. Young, D.P. Dykstra, and L.D. Garret. 1988. TEAMS: A decision support system for multiresource management. J. For. 86(8):25–33.
Falcão, A.O. and J.G. Borges. 2002. Combining random and systematic search heuristic procedures for solving spatially constrained forest management scheduling models. For. Sci. 48(3):608–621.
Falcão, A.O. and J.G. Borges. 2001. Designing an evolution program for solving integer forest management scheduling models: an application in Portugal. For. Sci. 47(2): 158–168.
Falcão, A., J.G. Borges and M. Tomé. 1999. sagFlor — an automated forest management prescription writer. In Timo Pukkala and K. Eerikainen (eds); Growth and yield modeling of tree plantations in South and East Africa, University of Joensuu, Faculty of Forestry Research Notes 97: 211–218.
Gunn, E.A. and A.K. Rai. 1987. Modeling and decomposition for planning long-term forest harvesting in an integrated industry structure. Can. J. For. Res. 17:1507–1518.
Hof, J.G. and L.A. Joyce. 1993. A mixed integer linear programming approach for spatially optimizing wildlife and timber in managed forest ecosystems. For. Sci. 39:816–834.
Hoganson, H.M. and D.W. Rose. 1984. A simulation approach for optimal timber management scheduling. For. Sci. 30:220–238.
Holland, J.H. 1975 Adaptation in natural and artificial systems. University of Michigan Press, Ann Harbor, MI.
Jones, J.G., B.J. Meneghin, and M.W. Kirby. 1991. Formulating adjacency constraints in linear optimization models for scheduling projects in tactical planning. For. Sci. 37:1283–1297.
Kirby, M.W. 1980. A guide to the integrated resources planning model. USDA For. Serv., Berkeley, California. 211 p.
Lappi, J. 1992. JLP, a linear programming package for management planning. The Finnish Forest Research Institute, Research Paper 414:1–134.
Lockwood, C., and T. Moore. 1993. Harvest scheduling with spatial constraints: a simulated annealing approach. Can. J. For. Res. 23:468–478.
Michalewicz, Z. 1996. Genetic algorithms + data structures = evolution programs (3rd ed.). Springer-Verlag, Berlin. 387 p.
Murray, A. and R. Church. 1995a. Heuristic solution approaches to operational forest planning problems. OR [Oper. Res.] Spektrum 17:193–203
Murray, A. and R. Church. 1995b. Measuring the efficacy of adjacency constraint structure in forest planning models. Can. J. For. Res. 25:1416–1424.
Nelson, J.D., and J.D. Brodie. 1990. Comparison of a random search algorithm and mixed integer programming for solving area-based forest plans. Can. J. For. Res. 20:934–942.
Pham, D.T. and D. Karaboga. 2000. Intelligent optimisation techniques. Genetic algorithms, tabu search, simulated annealing and neural networks. Springer-Verlag, London. 302 p.
Reeves, C.R. 1993. Modern heuristic techniques for combinatorial problems (1st ed.). John Wiley & Sons, Inc. New York. 320 p.
Snyder, S. and C. ReVelle. 1997. Dynamic selection of harvests with adjacency restrictions: the SHARe model. For. Sci. 43:213–222.
Tarp, P. and F. Helles. 1997. Spatial optimization by simulated annealing and linear programming. Scand. J. For. Res. 12:390–402.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer Science+Business Media Dordrecht
About this chapter
Cite this chapter
Falcão, A.O., Borges, J.G. (2003). Comparison of Heuristics for Spatially Constrained Natural Resource Management Problems. In: Arthaud, G.J., Barrett, T.M. (eds) Systems Analysis in Forest Resources. Managing Forest Ecosystems, vol 7. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-0307-9_26
Download citation
DOI: https://doi.org/10.1007/978-94-017-0307-9_26
Publisher Name: Springer, Dordrecht
Print ISBN: 978-90-481-6280-2
Online ISBN: 978-94-017-0307-9
eBook Packages: Springer Book Archive