57,518 research outputs found
Combining a hierarchical task network planner with a constraint satisfaction solver for assembly operations involving routing problems in a multi-robot context
This work addresses the combination of a symbolic hierarchical task network planner and a constraint satisfaction solver for the vehicle routing problem in a multi-robot context for structure assembly operations. Each planner has its own problem domain and search space, and the article describes how both planners interact in a loop sharing information in order to improve the cost of the solutions. The vehicle routing problem solver gives an initial assignment of parts to robots, making the distribution based on the distance among parts and robots, trying also to maximize the parallelism of the future assembly operations evaluating during the process the dependencies among the parts assigned to each robot. Then, the hierarchical task network planner computes a scheduling for the given assignment and estimates the cost in terms of time spent on the structure assembly. This cost value is then given back to the vehicle routing problem solver as feedback to compute a better assignment, closing the loop and repeating again the whole process. This interaction scheme has been tested with different constraint satisfaction solvers for the vehicle routing problem. The article presents simulation results in a scenario with a team of aerial robots assembling a structure, comparing the results obtained with different configurations of the vehicle routing problem solver and showing the suitability of using this approach.Unión Europea ARCAS FP7-ICT-287617Unión Europea H2020-ICT-644271Unión europea H2020-ICT-73166
An integrated assignment, routing, and speed model for roadway mobility and transportation with environmental, efficiency, and service goals
Managing all the mobility and transportation services with autonomous
vehicles for users of a smart city requires determining the assignment of the
vehicles to the users and their routing in conjunction with their speed. Such
decisions must ensure low emission, efficiency, and high service quality by
also considering the impact on traffic congestion caused by other vehicles in
the transportation network.
In this paper, we first propose an abstract trilevel multi-objective
formulation architecture to model all vehicle routing problems with assignment,
routing, and speed decision variables and conflicting objective functions. Such
an architecture guides the development of subproblems, relaxations, and
solution methods. We also propose a way of integrating the various urban
transportation services by introducing a constraint on the speed variables that
takes into account the traffic volume caused across the different services.
Based on the formulation architecture, we introduce a (bilevel) problem where
assignment and routing are at the upper level and speed is at the lower level.
To address the challenge of dealing with routing problems on urban road
networks, we develop an algorithm that alternates between the
assignment-routing problem on an auxiliary complete graph and the speed
optimization problem on the original non-complete graph. The computational
experiments show the effectiveness of the proposed approach in determining
approximate Pareto fronts among the conflicting objectives
A Novel Solution to the Dynamic Routing and Wavelength Assignment Problem in Transparent Optical Networks
We present an evolutionary programming algorithm for solving the dynamic
routing and wavelength assignment (DRWA) problem in optical wavelength-division
multiplexing (WDM) networks under wavelength continuity constraint. We assume
an ideal physical channel and therefore neglect the blocking of connection
requests due to the physical impairments. The problem formulation includes
suitable constraints that enable the algorithm to balance the load among the
individuals and thus results in a lower blocking probability and lower mean
execution time than the existing bio-inspired algorithms available in the
literature for the DRWA problems. Three types of wavelength assignment
techniques, such as First fit, Random, and Round Robin wavelength assignment
techniques have been investigated here. The ability to guarantee both low
blocking probability without any wavelength converters and small delay makes
the improved algorithm very attractive for current optical switching networks.Comment: 12 Pages, IJCNC Journal 201
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