Solving multi-objective optimization problems in conservation with the reference point method.

Iadine Chadès,Yann Dujardin

doi:10.1371/journal.pone.0190748

Iadine Chadès, Yann Dujardin

Open Access

https://doi.org/10.1371/journal.pone.0190748

Copy DOI

Abstract

Managing the biodiversity extinction crisis requires wise decision-making processes able to account for the limited resources available. In most decision problems in conservation biology, several conflicting objectives have to be taken into account. Most methods used in conservation either provide suboptimal solutions or use strong assumptions about the decision-maker’s preferences. Our paper reviews some of the existing approaches to solve multi-objective decision problems and presents new multi-objective linear programming formulations of two multi-objective optimization problems in conservation, allowing the use of a reference point approach. Reference point approaches solve multi-objective optimization problems by interactively representing the preferences of the decision-maker with a point in the criteria (objectives) space, called the reference point. We modelled and solved the following two problems in conservation: a dynamic multi-species management problem under uncertainty and a spatial allocation resource management problem. Results show that the reference point method outperforms classic methods while illustrating the use of an interactive methodology for solving combinatorial problems with multiple objectives. The method is general and can be adapted to a wide range of ecological combinatorial problems.

Highlights

In recent years, the benefits of using optimization methods to solve decision problems have been widely acknowledged in conservation biology
The control of disease across meta-populations can be optimized to ensure fastest recovery [10]. Such optimization methods are needed because decision problems are often combinatorial: the possible decisions we have to choose from are combination of smaller ones, which makes the number of possible decisions too large to attempt an exhaustive approach
We demonstrate the benefits of applying the reference point method to two classic combinatorial problems encountered in conservation: a dynamic multi-species decision problem under uncertainty [2] and a spatial resource allocation problem involving several objectives including biodiversity [16]

Summary

Introduction

The benefits of using optimization methods to solve decision problems have been widely acknowledged in conservation biology. Optimization methods have been developed to best allocate limited resources to protect threatened species [1], protect interacting species [2], design reserves [3, 4], eradicate invasive species [5], restore habitat [6] or translocate species [7]. The control of disease across meta-populations can be optimized to ensure fastest recovery [10]. Such optimization methods are needed because decision problems are often combinatorial: the possible decisions we have to choose from are combination of smaller ones, which makes the number of possible decisions too large to attempt an exhaustive approach (one cannot generate every possible decision and compare them).

Objectives

Methods

Conclusion