Changes between Version 3 and Version 4 of EwEugFishingPolicySearch
- Timestamp:
- 2010-02-08 00:17:13 (13 years ago)
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EwEugFishingPolicySearch
v3 v4 18 18 See [wiki:EwEugImplementingPolicyOptimizationInEcosim Implementing policy optimization] in Ecosim for help with implementing these two approaches in Ecosim. 19 19 20 ==== Policy objectives ==== 20 '''Policy objectives''' 21 21 22 Ecosim allows users to implement ‘open loop’ policy exploration simulations that acknowledges that policy may be defined as an approach towards reaching a broadly defined goal. The goal function for policy optimization is defined by the user in Ecosim, based on an evaluation of four weighted policy objectives: 22 23 … … 39 40 The fishing policy search routine estimates time series of relative fleet sizes that would maximize a multi-criterion objective function. In Ecosim, the relative fleet sizes are used to calculate relative fishing mortality rates by each fleet type, assuming the mix of fishing rates over biomass groups remains constant for each fleet type, (i.e., reducing a fleet type by some percentage results in the same percentage decrease in the fishing rates that it causes on all the groups that it catches). However, density-dependent catchability effects can be entered (using Ecosim’s Group info form), and if so reductions in biomass for a group may result in fishing rate remaining high despite reductions in total effort by any/all fleets that harvest it. Despite this caveat, the basic philosophy in the fishing policy search is that future management will be based on control of relative fishing efforts by fleet type, rather than on multispecies quota systems. It is not yet clear that there is any way to implement multispecies quotas safely anyway, without either using some arbitrary conservative rule like closing the fleet when it reaches the quota for the first (weakest) species taken or else allowing wasteful discarding of species once their quotas are reached. 40 41 41 ==== Optimization procedure ==== 42 '''Optimization procedure''' 43 42 44 Invoking the search option causes Ecosim to use a nonlinear optimization procedure known as the Davidson-Fletcher-Powell (DFP) method to iteratively improve an objective function by changing relative fishing rates, where each colour-coded ‘year/fleet block’ defines one parameter to be varied by the procedure (e.g. setting four colour code blocks means a 4-parameter nonlinear search). DFP runs the Ecosim model repeatedly while varying these parameters; in the search output display, each simulation trial is labelled an ‘eval’ or function evaluation. So if you are running a large model for many years, where each simulation takes several seconds to do, the search may take quite a long time to do enough function evaluations to find a maximum for the objective function. 43 45