Open AccessCOMPUTING OPTIMAL ALLOCATIONS FOR DISCRETE‐TIME NONLINEAR NATURAL RESOURCE MODELS
Author(s) -
Rowse John
Publication year - 1995
Publication title -
natural resource modeling
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.28
H-Index - 32
eISSN - 1939-7445
pISSN - 0890-8575
DOI - 10.1111/j.1939-7445.1995.tb00196.x
Subject(s) - non renewable resource , computer science , nonlinear system , resource (disambiguation) , natural resource , class (philosophy) , mathematical optimization , scale (ratio) , artificial intelligence , renewable energy , mathematics , ecology , computer network , physics , quantum mechanics , biology
Nonlinear programming (NLP) offers many advantages for formulating and solving discrete‐time nonlinear natural resource models. Not all natural resource analysts are aware of these advantages, however, and in this paper NLP approaches are discussed for a class of renewable resource models recently addressed in the literature using a current‐period decision rule approximation method, a class of nonrenewable resource models recently solved by first identifying the terminal extraction period, and related nonrenewable resource models. NLP can solve dynamic models ranging in size from small pedagogically‐oriented theoretical models to large‐scale policy evaluation models exhibiting many real‐world complications.