  Managing biodiversity extinction crisis requires wise decision-making
processes able to account for the limited of 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
space, called the reference point. We modelled and solved the following two
conservation problems: 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.
