8,103 research outputs found
A Two-Stage Approach for Routing Multiple Unmanned Aerial Vehicles with Stochastic Fuel Consumption
The past decade has seen a substantial increase in the use of small unmanned
aerial vehicles (UAVs) in both civil and military applications. This article
addresses an important aspect of refueling in the context of routing multiple
small UAVs to complete a surveillance or data collection mission. Specifically,
this article formulates a multiple-UAV routing problem with the refueling
constraint of minimizing the overall fuel consumption for all of the vehicles
as a two-stage stochastic optimization problem with uncertainty associated with
the fuel consumption of each vehicle. The two-stage model allows for the
application of sample average approximation (SAA). Although the SAA solution
asymptotically converges to the optimal solution for the two-stage model, the
SAA run time can be prohibitive for medium- and large-scale test instances.
Hence, we develop a tabu-search-based heuristic that exploits the model
structure while considering the uncertainty in fuel consumption. Extensive
computational experiments corroborate the benefits of the two-stage model
compared to a deterministic model and the effectiveness of the heuristic for
obtaining high-quality solutions.Comment: 18 page
A Constraint-directed Local Search Approach to Nurse Rostering Problems
In this paper, we investigate the hybridization of constraint programming and
local search techniques within a large neighbourhood search scheme for solving
highly constrained nurse rostering problems. As identified by the research, a
crucial part of the large neighbourhood search is the selection of the fragment
(neighbourhood, i.e. the set of variables), to be relaxed and re-optimized
iteratively. The success of the large neighbourhood search depends on the
adequacy of this identified neighbourhood with regard to the problematic part
of the solution assignment and the choice of the neighbourhood size. We
investigate three strategies to choose the fragment of different sizes within
the large neighbourhood search scheme. The first two strategies are tailored
concerning the problem properties. The third strategy is more general, using
the information of the cost from the soft constraint violations and their
propagation as the indicator to choose the variables added into the fragment.
The three strategies are analyzed and compared upon a benchmark nurse rostering
problem. Promising results demonstrate the possibility of future work in the
hybrid approach
Path Planning for Cooperative Routing of Air-Ground Vehicles
We consider a cooperative vehicle routing problem for surveillance and
reconnaissance missions with communication constraints between the vehicles. We
propose a framework which involves a ground vehicle and an aerial vehicle; the
vehicles travel cooperatively satisfying the communication limits, and visit a
set of targets. We present a mixed integer linear programming (MILP)
formulation and develop a branch-and-cut algorithm to solve the path planning
problem for the ground and air vehicles. The effectiveness of the proposed
approach is corroborated through extensive computational experiments on several
randomly generated instances
On green routing and scheduling problem
The vehicle routing and scheduling problem has been studied with much
interest within the last four decades. In this paper, some of the existing
literature dealing with routing and scheduling problems with environmental
issues is reviewed, and a description is provided of the problems that have
been investigated and how they are treated using combinatorial optimization
tools
GIS and Network Analysis
Both geographic information systems (GIS) and network analysis are burgeoning fields, characterised by rapid methodological and scientific advances in recent years. A geographic information system (GIS) is a digital computer application designed for the capture, storage, manipulation, analysis and display of geographic information. Geographic location is the element that distinguishes geographic information from all other types of information. Without location, data are termed to be non-spatial and would have little value within a GIS. Location is, thus, the basis for many benefits of GIS: the ability to map, the ability to measure distances and the ability to tie different kinds of information together because they refer to the same place (Longley et al., 2001). GIS-T, the application of geographic information science and systems to transportation problems, represents one of the most important application areas of GIS-technology today. While traditional GIS formulation's strengths are in mapping display and geodata processing, GIS-T requires new data structures to represent the complexities of transportation networks and to perform different network algorithms in order to fulfil its potential in the field of logistics and distribution logistics. This paper addresses these issues as follows. The section that follows discusses data models and design issues which are specifically oriented to GIS-T, and identifies several improvements of the traditional network data model that are needed to support advanced network analysis in a ground transportation context. These improvements include turn-tables, dynamic segmentation, linear referencing, traffic lines and non-planar networks. Most commercial GIS software vendors have extended their basic GIS data model during the past two decades to incorporate these innovations (Goodchild, 1998). The third section shifts attention to network routing problems that have become prominent in GIS-T: the travelling salesman problem, the vehicle routing problem and the shortest path problem with time windows, a problem that occurs as a subproblem in many time constrained routing and scheduling issues of practical importance. Such problems are conceptually simple, but mathematically complex and challenging. The focus is on theory and algorithms for solving these problems. The paper concludes with some final remarks.
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Centralized versus market-based approaches to mobile task allocation problem: State-of-the-art
Centralized approach has been adopted for finding solutions to resource allocation problems (RAPs) in many real-life applications. On the other hand, market-based approach has been proposed as an alternative to solve the problem due to recent advancement in ICT technologies. In spite of the existence of some efforts to review the pros and cons of each approach in RAPs, the studies cannot be directly applied to specific problem domains like mobile task allocation problem which is characterised with high level of uncertainty on the availability of resources (workers). This paper aims to review existing studies on task allocation problems(TAPs) focusing on those two approaches and their comparison and identify major issues that need to be resolved for comparing the two approaches in mobile task allocation problems. Mobile Task Allocation Problem (MTAP) is defined and its problematic structures are explained in relation with task allocation to mobile workers. Solutions produced by each approach to some applications and variations of MTAP are also discussed and compared. Finally, some future research directions are identified in order to compare both approaches in function of uncertainty emerging from the mobile nature of the MTAP
Operational Research in Education
Operational Research (OR) techniques have been applied, from the early stages of the discipline, to a wide variety of issues in education. At the government level, these include questions of what resources should be allocated to education as a whole and how these should be divided amongst the individual sectors of education and the institutions within the sectors. Another pertinent issue concerns the efficient operation of institutions, how to measure it, and whether resource allocation can be used to incentivise efficiency savings. Local governments, as well as being concerned with issues of resource allocation, may also need to make decisions regarding, for example, the creation and location of new institutions or closure of existing ones, as well as the day-to-day logistics of getting pupils to schools. Issues of concern for managers within schools and colleges include allocating the budgets, scheduling lessons and the assignment of students to courses. This survey provides an overview of the diverse problems faced by government, managers and consumers of education, and the OR techniques which have typically been applied in an effort to improve operations and provide solutions
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