  This paper addresses a generalization of the well known multi-agent path
finding (MAPF) problem that optimizes multiple conflicting objectives
simultaneously such as travel time and path risk. This generalization, referred
to as multi-objective MAPF (MOMAPF), arises in several applications ranging
from hazardous material transportation to construction site planning. In this
paper, we present a new multi-objective conflict-based search (MO-CBS) approach
that relies on a novel multi-objective safe interval path planning (MO-SIPP)
algorithm for its low-level search. We first develop the MO-SIPP algorithm,
show its properties and then embed it in MO-CBS. We present extensive numerical
results to show that (1) there is an order of magnitude improvement in the
average low level search time, and (2) a significant improvement in the success
rates of finding the Pareto-optimal front can be obtained using the proposed
approach in comparison with the previous MO-CBS.
