1,161 research outputs found
Efficient Multi-Robot Coverage of a Known Environment
This paper addresses the complete area coverage problem of a known
environment by multiple-robots. Complete area coverage is the problem of moving
an end-effector over all available space while avoiding existing obstacles. In
such tasks, using multiple robots can increase the efficiency of the area
coverage in terms of minimizing the operational time and increase the
robustness in the face of robot attrition. Unfortunately, the problem of
finding an optimal solution for such an area coverage problem with multiple
robots is known to be NP-complete. In this paper we present two approximation
heuristics for solving the multi-robot coverage problem. The first solution
presented is a direct extension of an efficient single robot area coverage
algorithm, based on an exact cellular decomposition. The second algorithm is a
greedy approach that divides the area into equal regions and applies an
efficient single-robot coverage algorithm to each region. We present
experimental results for two algorithms. Results indicate that our approaches
provide good coverage distribution between robots and minimize the workload per
robot, meanwhile ensuring complete coverage of the area.Comment: In proceedings of IEEE/RSJ International Conference on Intelligent
Robots and Systems (IROS), 201
Scheduling of Solid Waste Collection Routes
Routing of solid waste collection vehicles in Nigeria poses a challenging task because of attitudinal and haphazard infrastructure problems to contend with. The objective is to minimize the overall cost, which was essentially based on the distance travelled by collection vehicles. The study proposes heuristic methods to generate feasible solution to an extended capacitated Chinese Postman Problem (CCPP) in undirected network. The heuristic procedure consist of âroute first, cluster secondâ and âcluster first, route secondâ and was applied to scheduling solid waste collection problems in two cities â Abuja and Onitsha. The two techniques were compared and with the existing schedule with respect to cost, efficiency, and distance travelled. A cost model was developed to compare the quality of solution derived. The adoption of the proposed heuristics in Onitsha resulted in reduction of the number of existing vehicles by three, 31.10 (or 21.09%) of collection cost per day. Efficiency in refuse collection was increased from 86% to 98% in Abuja and 75% to 95% in Onitsha. The results revealed a good performance of the proposed heuristic methods which will find useful applications in other areas of vehicle scheduling
The Salesman's Improved Tours for Fundamental Classes
Finding the exact integrality gap for the LP relaxation of the
metric Travelling Salesman Problem (TSP) has been an open problem for over
thirty years, with little progress made. It is known that , and a famous conjecture states . For this problem,
essentially two "fundamental" classes of instances have been proposed. This
fundamental property means that in order to show that the integrality gap is at
most for all instances of metric TSP, it is sufficient to show it only
for the instances in the fundamental class. However, despite the importance and
the simplicity of such classes, no apparent effort has been deployed for
improving the integrality gap bounds for them. In this paper we take a natural
first step in this endeavour, and consider the -integer points of one such
class. We successfully improve the upper bound for the integrality gap from
to for a superclass of these points, as well as prove a lower
bound of for the superclass. Our methods involve innovative applications
of tools from combinatorial optimization which have the potential to be more
broadly applied
Self-Assembly of DNA Graphs and Postman Tours
DNA graph structures can self-assemble from branched junction molecules to yield solutions to computational problems. Self-assembly of graphs have previously been shown to give polynomial time solutions to hard computational problems such as 3-SAT and k-colorability problems. Jonoska et al. have proposed studying self-assembly of graphs topologically, considering the boundary components of their thickened graphs, which allows for reading the solutions to computational problems through reporter strands. We discuss weighting algorithms and consider applications of self-assembly of graphs and the boundary components of their thickened graphs to problems involving minimal weight Eulerian walks such as the Chinese Postman Problem and the Windy Postman Problem
Automated Functional Testing based on the Navigation of Web Applications
Web applications are becoming more and more complex. Testing such
applications is an intricate hard and time-consuming activity. Therefore,
testing is often poorly performed or skipped by practitioners. Test automation
can help to avoid this situation. Hence, this paper presents a novel approach
to perform automated software testing for web applications based on its
navigation. On the one hand, web navigation is the process of traversing a web
application using a browser. On the other hand, functional requirements are
actions that an application must do. Therefore, the evaluation of the correct
navigation of web applications results in the assessment of the specified
functional requirements. The proposed method to perform the automation is done
in four levels: test case generation, test data derivation, test case
execution, and test case reporting. This method is driven by three kinds of
inputs: i) UML models; ii) Selenium scripts; iii) XML files. We have
implemented our approach in an open-source testing framework named Automatic
Testing Platform. The validation of this work has been carried out by means of
a case study, in which the target is a real invoice management system developed
using a model-driven approach.Comment: In Proceedings WWV 2011, arXiv:1108.208
Spatial coverage in routing and path planning problems
Routing and path planning problems that involve spatial coverage have received increasing attention in recent years in different application areas. Spatial coverage refers to the possibility of considering nodes that are not directly served by a vehicle as visited for the purpose of the objective function or constraints. Despite similarities between the underlying problems, solution approaches have been developed in different disciplines independently, leading to different terminologies and solution techniques. This paper proposes a unified view of the approaches: Based on a formal introduction of the concept of spatial coverage in vehicle routing, it presents a classification scheme for core problem features and summarizes problem variants and solution concepts developed in the domains of operations research and robotics. The connections between these related problem classes offer insights into common underlying structures and open possibilities for developing new applications and algorithms
A -Approximation for Multiple TSP with a Variable Number of Depots
One of the most studied extensions of the famous Traveling Salesperson
Problem (TSP) is the {\sc Multiple TSP}: a set of salespersons
collectively traverses a set of cities by non-trivial tours, to
minimize the total length of their tours.
This problem can also be considered to be a variant of {\sc Uncapacitated
Vehicle Routing} where the objective function is the sum of all tour lengths.
When all tours start from a single common \emph{depot} , then the
metric {\sc Multiple TSP} can be approximated equally well as the standard
metric TSP, as shown by Frieze (1983).
The {\sc Multiple TSP} becomes significantly harder to approximate when there
is a \emph{set} of depots that form the starting and end points
of the tours.
For this case only a -approximation in polynomial time is known, as
well as a -approximation for \emph{constant} which requires a
prohibitive run time of (Xu and Rodrigues, \emph{INFORMS J.
Comput.}, 2015).
A recent work of Traub, Vygen and Zenklusen (STOC 2020) gives another
approximation algorithm for {\sc Multiple TSP} running in time
and reducing the problem to approximating TSP.
In this paper we overcome the time barrier: we give the first
efficient approximation algorithm for {\sc Multiple TSP} with a \emph{variable}
number of depots that yields a better-than-2 approximation.
Our algorithm runs in time , and produces a -approximation with
constant probability.
For the graphic case, we obtain a deterministic -approximation in time
.ithm for metric {\sc Multiple TSP} with run time
, which reduces the problem to approximating metric TSP.Comment: To be published at ESA 202
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