Applying revenue management to agent-based transportation planning

We consider a multi-company, less-than-truckload, dynamic VRP based on the concept of multi-agent systems. We focus on the intelligence of one vehicle agent and especially on its bidding strategy. We address the problem how to price loads that are offered in real-time such that available capacity is used in the most profitable way taking into account possible future revenues. We develop methods to price loads dynamically based on revenue management concepts.\ud We consider a one leg problem, i.e., a vehicle travels from i to j and can wait at most τ time units in which it can get additional loads from i to j. We develop a DP to price loads given a certain amount of remaining capacity and an expected number of auctions in the time-to-go. Because a DP might be impractical if parameters change frequently and bids has to be determined in real-time, we derived two approximations to speed up calculations. The performance of these approximations are compared with the performance of the DP. Besides we introduce a new measure to calculate the average vehicle utilisation in consolidated shipments. This measure can be calculated based on a limited amount of data and gives an indication of the efficiency of schedules and the performance of vehicles

Overlap-Minimization Scheduling Strategy for Data Transmission in VANET

The vehicular ad-hoc network (VANET) based on dedicated short-range communication (DSRC) is a distributed communication system, in which all the nodes share the wireless channel with carrier sense multiple access/collision avoid (CSMA/CA) protocol. However, the competition and backoff mechanisms of CSMA/CA often bring additional delays and data packet collisions, which may hardly meet the QoS requirements in terms of delay and packets delivery ratio (PDR). Moreover, because of the distribution nature of security information in broadcast mode, the sender cannot know whether the receivers have received the information successfully. Similarly, this problem also exists in no-acknowledge (non-ACK) transmissions of VANET. Therefore, the probability of packet collisions should be considered in broadcast or non-ACK working modes. This paper presents a connection-level scheduling algorithm overlaid on CSMA/CA to schedule the start sending time of each transmission. By converting the object of reducing collision probability to minimizing the overlap of transmission durations of connections, the probability of backoff-activation can be greatly decreased. Then the delay and the probability of packet collisions can also be decreased. Numerical simulations have been conducted in our unified platform containing SUMO, Veins and Omnet++. The result shows that the proposed algorithm can effectively improve the PDR and reduce the packets collision in VANET.Comment: 6 pages,7 figure

Towards Multi-Agent Simulation of the Dynamic Vehicle Routing Problem in MATSim

The paper presents the idea and the initial outcomes of integrating MATSim, a multi-agent transport simulation system, with the DVRP Optimizer, an application for solving the Dynamic Vehicle Routing Problem. First, the justification for the research is given and the state of the art is outlined. Then, MATSim is presented with a short description of the recent results in areas related to the one proposed in the paper, followed up by the discussion on the DVRP Optimizer functionality, architecture and implemented algorithms. Next, the process of integrating MATSim and the DVRP Optimizer is presented, with the distinction of two phases, the off-line and on-line optimization. Then, a description of the off-line optimization is given along with the results obtained for courier and taxi services in urban areas. The paper ends with conclusions and future plans

A framework for selecting strategies to impact the success of high volume roadway projects

State Highway Agencies (SHAs) are being forced to focus more on rehabilitation, resurfacing, and reconstruction of existing roadways rather than the construction of new facilities. These activities can create several challenges when they must be conducted on roadways with high traffic volumes. This research identified numerous strategies that can be implemented by SHAs that have the potential to influence the overall success of roadway projects with high traffic volumes. This research also created a framework for when to implement these different strategies. These strategies were identified through an in-depth literature review and through case studies conducted on highway projects that were under construction. Through the case studies the different strategies were documented within the context that warranted their use. Information from the case studies was collected and documented through interviews and site visits. The strategies identified through this research were used to create four matrices that summarize the research findings. A general matrix was created to show the motivating project conditions that warrant the use of each strategy. A public relations matrix was created to display the influence the impacted road user groups have on public relations and information strategies. A traffic management matrix was created to show different types of traffic management strategies and the potential impact they will have on the project. Finally, an interdependency matrix was created to show groups of strategies that are related to each other or require the use of other strategies to be able to influence the success of the project. These matrices could be further developed to create a set of guidelines that could be used by a SHA during the planning phases of a roadway project

Variable Data Collection Rate System for a Wildlife Behavior Monitor

Behavior monitors typically collect data, and consequently spend energy, at fixed intervals. For devices that utilize energy harvesting, a fixed data collection interval may result in inefficient battery usage due to variability in available solar radiation. Work was performed for a system capable of adjusting a data collection rate, proportional to changes in battery charge, such that data obtained was maximized without sacrificing battery energy sustainability. Energy consumption, of an actual behavior monitor, was modeled to aid in design and evaluation of a changeable data collection rate system. Model validation was performed by comparing simulated to empirical data for battery charge over time. Proportional Integral Derivative (PID) control was used that changed the rate at which data was collected such that error was minimized between battery State Of Charge (SOC) and a reference point. Gain scheduling was incorporated as a mechanism to resist change in data collection rate caused by fluctuation in available SOC. Gain parameters for a discrete, time domain, PID controller were tuned using a manual, trial and error method. Results of tuning showed improved performance with the absence of Integral control. The system was evaluated by performing simulations for change in available solar energy. Results showed that data collection adjusted to changes in available energy and as a consequence, SOC remained within +/-5% of a reference point

An optimization model for line planning and timetabling in automated urban metro subway networks

In this paper we present a Mixed Integer Nonlinear Programming model that we developed as part of a pilot study requested by the R&D company Metrolab in order to design tools for finding solutions for line planning and timetable situations in automated urban metro subway networks. Our model incorporates important factors in public transportation systems from both, a cost-oriented and a passenger-oriented perspective, as time-dependent demands, interchange stations, short-turns and technical features of the trains in use. The incoming flows of passengers are modeled by means of piecewise linear demand functions which are parameterized in terms of arrival rates and bulk arrivals. Decisions about frequencies, train capacities, short-turning and timetables for a given planning horizon are jointly integrated to be optimized in our model. Finally, a novel Math-Heuristic approach is proposed to solve the problem. The results of extensive computational experiments are reported to show its applicability and effectiveness to handle real-world subway networksComment: 30 pages, 6 figures, 9 table

algorithms for a vehicle routing tool supporting express freight delivery in small trucking companies

Abstract We present a tool to support the operations manager of small trucking companies. The tool integrates modules to manage pickup/delivery requests, determine initial assignment to trucks and service routes, react to dynamic events, support demand forecasting. Modules are interconnected by a cloud platform and take advantage from real-time data sharing. The core of the tool is a neighborhood search heuristic for a Vehicle Routing Problem with side attributes, to be solved in both static and dynamic settings. The efficiency of the algorithm is improved by enhanced search strategies, neighbor filtering and parallel implementation. A prototype implementation of the tool currently supports the operations at Trans-cel, a small freight transportation company. Tests on the field on different operational scenarios show that the algorithm fits both static and dynamic settings in terms of running times and quality of the suggested solutions