11,008 research outputs found
On Neighborhood Tree Search
We consider the neighborhood tree induced by alternating the use of different
neighborhood structures within a local search descent. We investigate the issue
of designing a search strategy operating at the neighborhood tree level by
exploring different paths of the tree in a heuristic way. We show that allowing
the search to 'backtrack' to a previously visited solution and resuming the
iterative variable neighborhood descent by 'pruning' the already explored
neighborhood branches leads to the design of effective and efficient search
heuristics. We describe this idea by discussing its basic design components
within a generic algorithmic scheme and we propose some simple and intuitive
strategies to guide the search when traversing the neighborhood tree. We
conduct a thorough experimental analysis of this approach by considering two
different problem domains, namely, the Total Weighted Tardiness Problem
(SMTWTP), and the more sophisticated Location Routing Problem (LRP). We show
that independently of the considered domain, the approach is highly
competitive. In particular, we show that using different branching and
backtracking strategies when exploring the neighborhood tree allows us to
achieve different trade-offs in terms of solution quality and computing cost.Comment: Genetic and Evolutionary Computation Conference (GECCO'12) (2012
A Hierarchal Planning Framework for AUV Mission Management in a Spatio-Temporal Varying Ocean
The purpose of this paper is to provide a hierarchical dynamic mission
planning framework for a single autonomous underwater vehicle (AUV) to
accomplish task-assign process in a limited time interval while operating in an
uncertain undersea environment, where spatio-temporal variability of the
operating field is taken into account. To this end, a high level reactive
mission planner and a low level motion planning system are constructed. The
high level system is responsible for task priority assignment and guiding the
vehicle toward a target of interest considering on-time termination of the
mission. The lower layer is in charge of generating optimal trajectories based
on sequence of tasks and dynamicity of operating terrain. The mission planner
is able to reactively re-arrange the tasks based on mission/terrain updates
while the low level planner is capable of coping unexpected changes of the
terrain by correcting the old path and re-generating a new trajectory. As a
result, the vehicle is able to undertake the maximum number of tasks with
certain degree of maneuverability having situational awareness of the operating
field. The computational engine of the mentioned framework is based on the
biogeography based optimization (BBO) algorithm that is capable of providing
efficient solutions. To evaluate the performance of the proposed framework,
firstly, a realistic model of undersea environment is provided based on
realistic map data, and then several scenarios, treated as real experiments,
are designed through the simulation study. Additionally, to show the robustness
and reliability of the framework, Monte-Carlo simulation is carried out and
statistical analysis is performed. The results of simulations indicate the
significant potential of the two-level hierarchical mission planning system in
mission success and its applicability for real-time implementation
Optimisation of Mobile Communication Networks - OMCO NET
The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University.
The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing
The trade-off between taxi time and fuel consumption in airport ground movement
Environmental impact is a very important agenda item in many sectors nowadays, which the air transportation sector is also trying to reduce
as much as possible. One area which has remained relatively unexplored in this context is the ground movement problem for aircraft on the airport’s surface.
Aircraft have to be routed from a gate to a runway and vice versa and it is
still unknown whether fuel burn and environmental impact reductions will best result from purely minimising the taxi times or whether it is also important to avoid multiple acceleration phases. This paper presents a newly developed multi-objective approach for analysing the trade-off between taxi time and fuel consumption during taxiing. The approach consists of a combination of a graph-based routing algorithm and a population adaptive immune algorithm to discover different speed profiles of aircraft. Analysis with data from a European hub airport has highlighted the impressive performance of the new approach. Furthermore, it is shown that the trade-off between taxi time and fuel consumption is very sensitive to the fuel-related objective function which is used
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