speed up multi-objective optimization

[jeffreyhanson]

The multi-objective optimization stuff can take a long time to run when a large emphasis is put on spatial clustering. To avoid this, one potential solution could be to use the solution obtained from the first part of the multi-objective optimizatin process as the starting solution for the second part of the multi-objective optimization. Unfortunately, of the solvers currently supported by prioritizr, only the commercial solvers currently let us specify a starting solution. As such, we would need to (1) update the R package for the FOSS solvers (e.g. Rsymphony or rcbc), and (2) update the corresponding prioritizr function used to access the solver (e.g. add_rsymphony_solver or add_cbc_solver) --- which could be a fair amount of work.

[jeffreyhanson]

Closing this because it is a duplicate of #139