  Max-min approaches have been widely applied to address equity as an essential
consideration in humanitarian operations. These approaches, however, have a
significant drawback of being neutral when it comes to solutions with the same
minimum values. These equivalent solutions, from a max-min point of view, might
be significantly different. We address this problem using the lexicographic
maximin approach, a refinement of the classic max-min approach. We apply this
approach in the rapid needs assessment process, which is carried out
immediately after the onset of a disaster, to investigate the disaster's impact
on the affected community groups through field visits. We construct routes for
an assessment plan to cover community groups, each carrying a distinct
characteristic, such that the vector of coverage ratios are maximized. We
define the leximin selective assessment problem, which considers the
bi-objective optimization of total assessment time and coverage ratio vector
maximization. We solve the bi-objective problem by a heuristic approach based
on the multi-directional local search framework.
