5,021 research outputs found
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
Dynamic planning of mobile service teams’ mission subject to orders uncertainty constraints
This paper considers the dynamic vehicle routing problem where a fleet of vehicles deals with periodic deliveries of goods or services to spatially dispersed customers over a given time horizon. Individual customers may only be served by predefined (dedicated) suppliers. Each vehicle follows a pre-planned separate route linking points defined by the customer location and service periods when ordered deliveries are carried out. Customer order specifications and their services time windows as well as vehicle travel times are dynamically recognized over time. The objective is to maximize a number of newly introduced or modified requests, being submitted dynamically throughout the assumed time horizon, but not compromising already considered orders. Therefore, the main question is whether a newly reported delivery request or currently modified/corrected one can be accepted or not. The considered problem arises, for example, in systems in which garbage collection or DHL parcel deliveries as well as preventive maintenance requests are scheduled and implemented according to a cyclically repeating sequence. It is formulated as a constraint satisfaction problem implementing the ordered fuzzy number formalism enabling to handle the fuzzy nature of variables through an algebraic approach. Computational results show that the proposed solution outperforms commonly used computer simulation methods
Vehicle Routing Problem in Cold Chain Logistics: a Joint Distribution Model with Carbon Trading Mechanisms
Fierce competition and the mandate for green development have driven cold chain logistics companies to minimize total distribution costs and carbon emissions to gain a competitive advantage and achieve sustainable development. However, the cold chain logistics literature considers carbon trading mechanisms in sharing economy, namely the joint distribution, is limited. Our research builds a Joint Distribution-Green Vehicle Routing Problem (JD-GVRP) model, in which cold chain logistics companies collaborate among each other to deliver cold chain commodities by considering carbon tax policy. Based on the real business data from four cold chain companies and 28 customers, a simulated annealing (SA) algorithm is applied to optimize the model. The results indicate that joint distribution is an effective way to reduce total costs and carbon emissions when compared with the single distribution. The total cost is positively correlated with the carbon price, while the carbon emissions vary differently when the carbon price increases. In addition, carbon quotas have no effect on the delivery path. This research expands cold chain logistics literature by linking it with joint distribution and carbon trading mechanisms. Moreover, this research suggests that cold chain logistics companies could enhance delivery efficiency, reduce the business cost, and improve competitiveness by reinforcing the collaboration at the industry level. Furthermore, the government should advocate the mode of joint distribution and formulate an effective carbon trading policy to better utilize social and industrial resources to achieve the balanced economic and environmental benefits
Base and surge strategies for controlling environmental and economic costs in logistics triads
The aim of this paper is to determine the extent to which it is possible to establish a ‘base’ and ‘surge’ strategy for logistics provision with a particular emphasis on minimising environmental and economic costs. Our method is the combination of empirical research outputs on the impact of uncertainty on economic and environmental costs, and a synthesis of the literature on resilience and the role of flexibility therein. We find that logistics planners either build contingents into their schedules (a priori) or that they respond with contingencies (a posteriori). The former is associated with a ‘base‘ approach; an example of which may be the incorporation of ‘slack time‘ into a schedule to accommodate expected delays due to road congestion. The latter is equivalent to a ‘surge‘ approach where as an example the logistics provider may have capacity flexibility, in the form of spare vehicles, to accommodate post-plan changes in shipper volume requirements. This paper explicitly rationalises the links between uncertainty, ‘base’ and ‘surge’ supply chain strategies, and the strategic use of logistics flexibility, in minimising environmental and economic costs in a logistics triad. The output is in the form of a conceptual managerial feedback control system
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
Traffic Management System for the combined optimal routing, scheduling and motion planning of self-driving vehicles inside reserved smart road networks
The topic discussed in this thesis belongs to the field of automation of transport
systems, which has grown in importance in the last decade, both in the innovation
field (where different automation technologies have been gradually introduced in
different sectors of road transport, in the promising view of making it more efficient,
safer, and greener) and in the research field (where different research activities and
publications have addressed the problem under different points of view).
More in detail, this work addresses the problem of autonomous vehicles coordina tion inside reserved road networks by proposing a novel Traffic Management System
(TMS) for the combined routing, scheduling and motion planning of the vehicles.
To this aim, the network is assumed to have a modular structure, which results from
a certain number of roads and intersections assembled together. The way in which
roads and intersections are put together defines the network layout. Within such a
system architecture, the main tasks addressed by the TMS are: (1) at the higher
level, the optimal routing of the vehicles in the network, exploiting the available
information coming from the vehicles and the various elements of the network; (2)
at a lower level, the modeling and optimization of the vehicle trajectories and speeds
for each road and for each intersection in the network; (3) the coordination between
the vehicles and the elements of the network, to ensure a combined approach that
considers, in a recursive way, the scheduling and motion planning of the vehicles in
the various elements when solving the routing problem.
In particular, the routing and the scheduling and motion planning problems are
formulated as MILP optimization problems, aiming to maximize the performance
of the entire network (routing model) and the performance of its single elements -
roads and intersections (scheduling and motion planning model) while guaranteeing
the requested level of safety and comfort for the passengers.
Besides, one of the main features of the proposed approach consists of the integration of the scheduling decisions and the motion planning computation by means of constraints regarding the speed limit, the acceleration, and the so-called safety
dynamic constraints on incompatible positions of conflicting vehicles. In particular,
thanks to these last constraints, it is possible to consider the real space occupancy
of the vehicles avoiding collisions.
After the theoretical discussion of the proposed TMS and of its components
and models, the thesis presents and discusses the results of different numerical experiments, aimed at testing the TMS in some specific scenarios. In particular, the
routing model and the scheduling and motion planning model are tested on different scenarios, which demonstrate the effectiveness and the validity of such approach
in performing the addressed tasks, also compared with more traditional methods.
Finally, the computational effort needed for the problem solution, which is a key element to take into account, is discussed both for the road element and the intersection element
- …