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Decision Support System For Integrated Door-to-door Delivery:planning And Control In Logistic Chains

Exploitable results

The 'Decision support system for integrated door-to-door delivery: planning and control in logistic chains' (MOSCA) project results are tools aiming to improve the efficiency of door-to-door transport of goods in urban areas by providing both demand and supply information. This set of tools provides services such as finding the shortest path, on-line vehicle routing planning, delivery planning, etc. for private and public operators. More specifically, the MOSCA decision support system consists of several modules that communicate not only with each other, but also with external systems. These software modules which have been designed to assist authorities in planning, assessing and controlling freight transport are: Mosca-Freight: this module allows for the calculation of business traffic and freight transport demand matrices over a city or region. Data collection/processing will depend on the availability of behavioural data and the definition of business traffic classes. Nonetheless, it can be integrated in a holistic modelling framework which may include a passenger transport demand model such as Viseva and a network/assignment model such as VISUM. Therefore, detailed analyses of commercial transport against passenger transport are possible with the use of this modelling framework. Mosca-Sustain: this module allows for the calculation of noise emissions and the corresponding social costs. While a rather high amount of data input is necessary, it possible to obtain accurate estimations of the real noise levels. Mosca-Short: this heuristic algorithm for finding the robust shortest path is suitable for application to real problems. The concept of robust path, which has been applied here for the first time to road network problems, can ensure accurate results. More specifically, the results of tests conducted during the course of the MOSCA project suggest that it is the fastest algorithm available at present to solve robust shortest path problems, at least on road networks. Mosca-Net: a web service to identify the preferred delivery locations for recipients of freight consignments. Mosca-Net receives information about delivery locations, delivery profiles and time windows from business to consumer (B2C), i.e. private customers. Customers can connect to this module's database and store the necessary information using the dedicated user interface. The information on delivery location and time windows is given upon request. Its primary objective is to serve as an information hub for delivery data, which can be accessed by private customers and logistics service providers. Mosca-Line: an algorithm to plan online deliveries, especially in the case of unexpected events such as a new customer request or a traffic jam. Mosca-Line is able to reorganise the next stops, given the current position of vehicles, the road network situation and the list of orders to be processed. This module can also gather information about the traffic conditions based on information communicated by the vehicles and it can use this information to produce better plans that are more suitable for new traffic situations. Mosca-Shop: a web service to schedule the reservation of access ramps for urban freight deliveries. Mosca-Shop provides information on free docks and allows booking of specific time slots. It can be used by carriers to plan the waiting times at the shops' loading dock. They enter shipment data and place dock booking requests. On the other hand, shops can provide information about their accessibility and instructions for carriers. Using the Mosca-Shop module will pass the dock accessibility schedule and delivery instructions to the carrier and the incoming booking requests to the shop. Mosca-Tour: an algorithm to plan the delivery tours for a vehicle fleet based on the available information about the variable traffic conditions. Mosca-Tour is embedded into a logistics application software, which is supplied with data on the orders to be serviced, the objective function, and the characteristics of the vehicles' fleet. Distances and travel times can be provided either by Mosca-Short or a traffic model. After receiving all input data, the algorithm calculates the most cost-efficient vehicle routes. The result is a set of optimised routes that is sent back to the logistics application software.

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