The city of Asheville, NC is seeking to improve access to its parks. In this deliverable, your team

will formulate three optimization models to recommend locations for new parks. These

conditions are hypothetical and inspired by real$-$world context on park planning.

You will develop optimization models to recommend locations with the following

characteristics:

Locate $p$ new parks to minimize the total demand$-$weighted distance all people will

need to travel to their nearest park.

Locate $p$ new parks to minimize the furthest distance a person will need to travel to

their nearest park.

Locate $p$ new parks while trading off the two objectives above.

Include sections for the following:

Sets

Parameters

Model formulation

Formulation description

The formulation description should be a paragraph that briefly notes what

each constraint does. E$.$g$.,$ constraint set $(4)$ limits $...$

Additional Modeling Context

The eligible park locations are given in set $J,$ and the locations people live are given in set I.

Within set $J,$ there are existing parks within the city $(J^{\text{e}\text{x}\text{i}\text{s}\text{t}\text{i}\text{n}\text{g}}$subJ$)$ and candidate parks

$(J^{\text{c}\text{a}\text{n}\text{d}\text{i}\text{d}\text{a}\text{t}\text{e}}$subJ$)$ that could be located. People can either be closest to an existing park or one of

the $p$ new parks you will recommend be located.

Total demand$-$weighted distance represents the park distance multiplied by the number of people

who have to travel that far. E$.$g$.,$ if $10$ people live $1$ mile from a park and $5$ people live $3$ miles

from a park, the total demand$-$weighted distanced is $25$ people$-$miles $(={10}^{**}1+5^{**}3).$