Many interesting search problems can be formulated as bi-objective search problems, that
is, search problems where two kinds of costs have to be minimized, for example, travel …

In the multi-objective shortest-path problem we are interested in computing a path, or a set of
paths that simultaneously balance multiple cost functions. This problem is important for a …

Multi-objective search can be used to model many real-world problems that require finding
Paretooptimal paths from a specified start state to a specified goal state, while considering …

Abstract In the Multi-Objective Shortest Path Problem (MO-SPP), one has to find paths on a
graph that simultaneously minimize multiple objectives. It is not guaranteed that there exists …

Abstract Contraction Hierarchies (CHs) have been successfully used as a preprocessing
technique in single-objective graph search for finding shortest paths. However, only a few …

When a robot autonomously performs a complex task, it frequently must balance competing
objectives while maintaining safety. This becomes more difficult in uncertain environments …

Abstract The Multi-Objective Multi-Agent Path Finding (MO-MAPF) problem is the problem of
computing collision-free paths for a team of agents while minimizing multiple cost metrics …

Bi-objective search problems are a useful generalization of shortest path search. This paper
reviews some recent contributions for the solution of this problem with emphasis on the …

Abstract In the Weight-Constrained Shortest-Path (WCSP) problem, given a graph in which
each edge is annotated with a cost and a weight, a start state, and a goal state, the task is to …

In the multi-objective search problem, a typical task is to compute the Pareto frontier, ie, the
set of all undominated solutions. However, computing the entire Pareto frontier can be very …