Abstract parameters such as vehicle capacity, seasonal variations

Abstract SummaryThis article is about easily operatable web-based spatial decision support system (webSDSS) focus on creating optimized vehicle routes for multiple vehicle routing problems. The web-SDSS contain Google Maps™, a database management component, a heuristic and a system developed by the author to make routes and detailed vehicle route maps. It contains realistic approach, such as vehicle capability and shifts time constrictions, as well as the network problems such as one-way, two-ways restrictions and prohibited attributes. webSDSS can be used for “what-if” analysis, the input parameters such as vehicle capacity, seasonal variations of demand maximum driving time shift, and network Constraints are related to change. Only it needs a web browser, it is easy to adopt widely and is used in many real-world scenarios. The system developed was experimentally used for urban trash collection in the Coimbra, Portugal. 1. Introduction Summary1.1. The importance and impacts of vehicle routing problems :In both sectors public and private the transportation of goods, Stuff and services are very considerable both environmental and economic point of view. Every industry wants efficient and fast access to the public , and no one can neglect the importance of efficient vehicle routing in this regard, because due to this it can reduce energy consumption, air pollution, and its truly a very big problem in almost all urban areas, mainly the vehicle miles of travel (VMT) increase causing such type of vehicle routing problems. So there is an impact of vehicle routing problem on economic activities but also, on the other hand, there is an environmental impact. In an urban context, if the number of the vehicle increase the traffic congestion, noise and air pollution level increase.The main approach which is built as for as environmental impact is concern the consumption of lowest number of fuel to minimize emission of CO2, and decreasing VMT can minimize carbon emission. Reducing VMT have an important impact on public health.  So to address all the issues discussed above there is a need for developing spatial decision support system for decision supporting purposes, this paper contains the methodological implementation of web-based spatial decision support system (webSDSS).1.2 DSS and ICT in transportation problems:Due to the complex problems in urban planning and transportation and data requirements there has been very rapid growth in use of decision support systems (DSS) to analyse data at expert level. These problem have spatial nature due to which geographical information system (GIS) is important component of such DSS, as GIS deals mainly with spatial data in planning major such as vehicle routing problem. WWW technologies have modified the layout, development, and deployment of DSS. Ray has formed a web-based spatial DSS for controlling the transportation of oversize and extra weighted vehicles over highways. Also the importance of ICT, besides GIS technology, is recognized in various fields related to transportation. The Internet permits the implementation of web-based GIS systems, allowing users to communicate with tracks, maps, and GIS tools through a web browser. Thus, investigating this particular ICT ability granted by the Internet linked with Google Maps™ services is an assuring avenue for generating web-based spatial DSS including specific algorithms for routing optimization problems.2 The aim of this research (Summary):In this article, authors present a web-SDSS different methodologies which is design for multiple vehicle routing problems. The system was tested in real world routing problem. The system can be used in both private and public sector to solve vehicle routing problems. Whole web-SDSS design contain first creating vehicles collection routes, the routes can be change seasonally or even daily. Second the system must be very user-friendly so that anyone can use it. Third, the system must generate single route maps and direction instruction for the driver. Fourth, the web-SDSS must incorporate in local network. Fifth, the system must be capable to analyse long term decisions. And finally, the designed web-SDSS is unique and universal to be used in every part of the world through internet (Google Map) on browser.3 Background: Vehicle routing is common problem faced by private and public sector companies, with economic, social and environmental aspects. The implemented web-SDSS solve many real-world routing problems . Examples include the collection/distribution of goods along streets, pipe or road inspection, water, gas, and electricity meter reading, mail delivery, street cleaning, and the collection of urban solid waste. These application can be structured as a capacitated arc routing problem (CARP). The algorithms for CARP weretaken as good opening tools for implementation of webSDSS dedicated to vehicle routing problems. Other general requirements includes in the development of webSDSS is access to digital maps and network data, the development of web tool which only require an Internet browser. the human–computer graphical interface, access to cartography, Google Maps™ is best tool due to its universal availability via web and access to remote road network dataset.4 Architecture of the webSDSS     4.1 Implementation detailsImplementation design includes input, output and other planning and analytical capabilities, these includes generating route maps, solution algorithm, other vehicle route detailed information in tabular form using internet browser. In order to achieve our objective, the webSDSS need data and other analysis and modelling capabilities. Google Map is most appropriate . the data for each route problem is stored in database which will be developed using Microsoft SQL Server, java and C# programming languages were used to develop system. The user can access to web browser.  WebSDSS Interface:The interface which is supported by a standard browser in which map is in center of the screen. In the top bar there are four menus: “Edit Networks,” “Shortest Paths,” “Solve Problem” and “Show Results”. On the left head side bar there is editable fields for inputting of data. A right-hand sidebar supports lists with the representation of results available after solving a problem (as described in Section 3.4 (Screenshot) ).WebSDSS input:The system includes different menus one is for input data edition. Problem parameters time and service or related to vehicles (such as maximum shift times, capacities, relative costs) can be edited in the webSDSS environment using the respective boxes that are shown on the left-hand bar afterselecting an input in a main menu (as shown in Fig. 2). the user can freely edit those parameters. The values of other parameters, arc demand and arc orientation, as arc service time, can also be edit by the user. Calculating shortest path for shortest path menu all restrictions , one way street etc are considered in the shortest path calculations by using network data provided by GoogleMaps™. After calculation, the shortest route are stored in the database.  WebSDSS output:The output of webSDSS is efficient vehicle routes including graphical maps. It determine number of route and vehicles, it also model individual routes. Show routes” on the menu “Show results” displays a list containing routes on the left-hand sidebar, click on a specific route of that list, the route is displayed on the map (Fig. 4), where colour (orange) lines represent on the route that do not include pickups, and colour (red) lines represent served arcs of the displayed route.Result and discussion:Complex decision problems generally required Sensitivity and what-if analysis. In vehicle routing problems it is usually interesting to obtain answers about the impact of changes on the required resource. In the example, results were obtained (solution S1) by solving the problem with a shift limit of 6 h (Table 1) for two types of vehicles with different capabilities. Five routes were generated, organized in three shifts for vehicle type B and one shift for vehicle type A. The objective is minimization of the total travelled vehicle length. See table. As demonstrated, the implemented webSDSS can be used for both short-term analysis and long term analysis only requiring an web browser .  Summary and conclusions: The web-based spatial decision support system developed by authors for the vehicle routing problems entirely access thought web browser. Internet browser used that allow remotely access algorithms, network data and cartography. Google map represents solution route models with a list of direction in sequence. Although the webSDSS was tested for an urban trash collection situation, which is an important problem in urban area, this system can be used in other real-world problems of capacitated routing (e.g., street