scholarly journals Exact integer linear programming solvers outperform simulated annealing for solving conservation planning problems

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e9258
Author(s):  
Richard Schuster ◽  
Jeffrey O. Hanson ◽  
Matthew Strimas-Mackey ◽  
Joseph R. Bennett

The resources available for conserving biodiversity are limited, and so protected areas need to be established in places that will achieve objectives for minimal cost. Two of the main algorithms for solving systematic conservation planning problems are Simulated Annealing (SA) and exact integer linear programing (EILP) solvers. Using a case study in BC, Canada, we compare the cost-effectiveness and processing times of SA used in Marxan versus EILP using both commercial and open-source algorithms. Plans for expanding protected area systems based on EILP algorithms were 12–30% cheaper than plans using SA, due to EILP’s ability to find optimal solutions as opposed to approximations. The best EILP solver we examined was on average 1,071 times faster than the SA algorithm tested. The performance advantages of EILP solvers were also observed when we aimed for spatially compact solutions by including a boundary penalty. One practical advantage of using EILP over SA is that the analysis does not require calibration, saving even more time. Given the performance of EILP solvers, they can be used to generate conservation plans in real-time during stakeholder meetings and can facilitate rapid sensitivity analysis, and contribute to a more transparent, inclusive, and defensible decision-making process.

2019 ◽  
Author(s):  
Richard Schuster ◽  
Jeffrey O. Hanson ◽  
Matt Strimas-Mackey ◽  
Joseph R. Bennett

AbstractThe resources available for conserving biodiversity are limited, and so protected areas need to be established in places that will achieve objectives for minimal cost. Two of the main algorithms for solving systematic conservation planning problems are Simulated Annealing (SA) and Integer linear programming (ILP). Using a case study in British Columbia, Canada, we compare the cost-effectiveness and processing times of SA versus ILP using both commercial and open-source algorithms. Plans for expanding protected area systems based on ILP algorithms were 12 to 30% cheaper than plans using SA. The best ILP solver we examined was on average 1071 times faster than the SA algorithm tested. The performance advantages of ILP solvers were also observed when we aimed for spatially compact solutions by including a boundary penalty. One practical advantage of using ILP over SA is that the analysis does not require calibration, saving even more time. Given the performance of ILP solvers, they can be used to generate conservation plans in real-time during stakeholder meetings and can facilitate rapid sensitivity analysis, and contribute to a more transparent, inclusive, and defensible decision-making process.


2021 ◽  
Vol 39 (3) ◽  
Author(s):  
Paloma Taltavull ◽  
Raúl Pérez ◽  
Francisco Juárez

The article addresses the relevance of the real estate sector in climate change control through the decarbonisation of buildings. It presents a case study of an investment portfolio artificially constructed from randomly selected buildings in different Spanish cities and with different uses, evaluated in terms of their structural and energy characteristics. The CRREM tool is used to evaluate the decarbonisation horizon of the buildings between 2018 and 2050, their total emissions and their cost, in relation to the maximum allowed in the agreements signed by the EU in Paris (COP21). From this calculation, an assessment is provided of when buildings will become energetically stranded (energy obsolete) assets and the cost of carbon emitted above permitted levels. These calculations lend transparency to the investment decision-making process facing building owners in the EU over the next 30 years.


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