3,861 research outputs found
A Constraint Programming Approach for Non-Preemptive Evacuation Scheduling
Large-scale controlled evacuations require emergency services to select
evacuation routes, decide departure times, and mobilize resources to issue
orders, all under strict time constraints. Existing algorithms almost always
allow for preemptive evacuation schedules, which are less desirable in
practice. This paper proposes, for the first time, a constraint-based
scheduling model that optimizes the evacuation flow rate (number of vehicles
sent at regular time intervals) and evacuation phasing of widely populated
areas, while ensuring a nonpreemptive evacuation for each residential zone. Two
optimization objectives are considered: (1) to maximize the number of evacuees
reaching safety and (2) to minimize the overall duration of the evacuation.
Preliminary results on a set of real-world instances show that the approach can
produce, within a few seconds, a non-preemptive evacuation schedule which is
either optimal or at most 6% away of the optimal preemptive solution.Comment: Submitted to the 21st International Conference on Principles and
Practice of Constraint Programming (CP 2015). 15 pages + 1 reference pag
An Order-based Algorithm for Minimum Dominating Set with Application in Graph Mining
Dominating set is a set of vertices of a graph such that all other vertices
have a neighbour in the dominating set. We propose a new order-based randomised
local search (RLS) algorithm to solve minimum dominating set problem in
large graphs. Experimental evaluation is presented for multiple types of
problem instances. These instances include unit disk graphs, which represent a
model of wireless networks, random scale-free networks, as well as samples from
two social networks and real-world graphs studied in network science. Our
experiments indicate that RLS performs better than both a classical greedy
approximation algorithm and two metaheuristic algorithms based on ant colony
optimisation and local search. The order-based algorithm is able to find small
dominating sets for graphs with tens of thousands of vertices. In addition, we
propose a multi-start variant of RLS that is suitable for solving the
minimum weight dominating set problem. The application of RLS in graph
mining is also briefly demonstrated
Heuristics for Network Coding in Wireless Networks
Multicast is a central challenge for emerging multi-hop wireless
architectures such as wireless mesh networks, because of its substantial cost
in terms of bandwidth. In this report, we study one specific case of multicast:
broadcasting, sending data from one source to all nodes, in a multi-hop
wireless network. The broadcast we focus on is based on network coding, a
promising avenue for reducing cost; previous work of ours showed that the
performance of network coding with simple heuristics is asymptotically optimal:
each transmission is beneficial to nearly every receiver. This is for
homogenous and large networks of the plan. But for small, sparse or for
inhomogeneous networks, some additional heuristics are required. This report
proposes such additional new heuristics (for selecting rates) for broadcasting
with network coding. Our heuristics are intended to use only simple local
topology information. We detail the logic of the heuristics, and with
experimental results, we illustrate the behavior of the heuristics, and
demonstrate their excellent performance
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