Systematic conservation planning (Margules and Pressey 2000) has been widely recognized as a coherent framework for informing decision makers about conservation problems regarding protected area design and management effectiveness. Creating a system of protected areas is the most common form of systematic conservation planning. The problem considered here is one of multi-objective optimization, where decisions need to be taken in the presence of trade-offs between two or more conflicting objectives, how address decision in trade-offs objective costs.
To overcome the above-mentioned limitation of trade-off multi-objective optimization problem, we propose a Flexible Multi-objective Optimum Conservation Planning(FMOCP) model in this research.
Detailed descriptions of each step in FMOCP are given below. Optimization model formulations There are Three objectives and two constraints considered in this optimization model. Their detailed formulations are described as follows: Objectives: Objective 1: Maximize Agricultural suitability Objective 2: Minimize Forest disaster occurrence rate Objective 3: Maximize Ecologically sensitive species habitat Objective 4: Maximize Spatial compactness.
Results/Conclusions
For exploration of the trade-offs between multiple objectives a “Pareto optimal” solutions method is employed. The model provides explicit insight in the trade-off between the objectives of alternative options. It can be applied to a range of spatially multi-objective decision make in conservation region problems and will further evolve as a result of anticipated interactions with stakeholders.
In face of the multiple choices for conservation, the main issue is to identify those that prove to be the more effective and reliable in the long term. In this work, a simulation-based multi-objective optimization scheme is employed of a conservation. A case study is used to demonstrate the functionality of the proposed approach. The results verify the practicability of the approach and highlight potential problems that may arise.