1,656 research outputs found

    An ontology-based spatial group decision support system for site selection application

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    This paper presents a new ontology-based multicriteria spatial group decision support system (GDSS) dedicated to site selection problems. Site selection is one of the most complex problems in the construction of a new building. It presents a crucial problem in terms of selecting the appropriate site among a group of decision makers with multiple alternatives (sites); in addition, the site must satisfy several criteria. To deal with this, the present paper introduces an ontology based multicriteria analysis method to solve semantic heterogeneity in vocabulary used by participants in spatial group decision support systems. The advantages of using ontology in GDSS are many: i) it enables the integration of heterogeneous sources of data available on the web and ii) it enables to facilitate meaning and sharing of data used in GDSS by participants. In order to facilitate cooperation and collaboration between participants in GDSS, our work aims to apply ontology at the model's structuration phase. The proposed system has been successfully implemented and exploited for a personalized environment

    Collection and integration of local knowledge and experience through a collective spatial analysis

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    This article discusses the convenience of adopting an approach of Collective Spatial Analysis in the P/PGIS processes, with the aim of improving the collection and integration of knowledge and local expertise in decision-making, mainly in the fields of planning and adopting territorial policies. Based on empirical evidence, as a result of the review of scientific articles from the Web of Science database, in which it is displayed how the knowledge and experience of people involved in decision-making supported by P/PGIS are collected and used, a prototype of a WEB-GSDSS application has been developed. This prototype allows a group of people to participate anonymously, in an asynchronous and distributed way, in a decision-making process to locate goods, services, or events through the convergence of their views. Via this application, two case studies for planning services in districts of Ecuador and Italy were carried out. Early results suggest that in P/PGIS local and external actors contribute their knowledge and experience to generate information that afterwards is integrated and analysed in the decision-making process. On the other hand, in a Collective Spatial Analysis, these actors analyse and generate information in conjunction with their knowledge and experience during the process of decision-making. We conclude that, although the Collective Spatial Analysis approach presented is in a subjective and initial stage, it does drive improvements in the collection and integration of knowledge and local experience, foremost among them is an interdisciplinary geo-consensusPeer ReviewedPostprint (published version

    Development of transportation and supply chain problems with the combination of agent-based simulation and network optimization

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    Demand drives a different range of supply chain and logistics location decisions, and agent-based modeling (ABM) introduces innovative solutions to address supply chain and logistics problems. This dissertation focuses on an agent-based and network optimization approach to resolve those problems and features three research projects that cover prevalent supply chain management and logistics problems. The first case study evaluates demographic densities in Norway, Finland, and Sweden, and covers how distribution center (DC) locations can be established using a minimizing trip distance approach. Furthermore, traveling time maps are developed for each scenario. In addition, the Nordic area consisting of those three countries is analyzed and five DC location optimization results are presented. The second case study introduces transportation cost modelling in the process of collecting tree logs from several districts and transporting them to the nearest collection point. This research project presents agent-based modelling (ABM) that incorporates comprehensively the key elements of the pick-up and delivery supply chain model and designs the components as autonomous agents communicating with each other. The modelling merges various components such as GIS routing, potential facility locations, random tree log pickup locations, fleet sizing, trip distance, and truck and train transportation. The entire pick-up and delivery operation are modeled by ABM and modeling outcomes are provided by time series charts such as the number of trucks in use, facilities inventory and travel distance. In addition, various scenarios of simulation based on potential facility locations and truck numbers are evaluated and the optimal facility location and fleet size are identified. In the third case study, an agent-based modeling strategy is used to address the problem of vehicle scheduling and fleet optimization. The solution method is employed to data from a real-world organization, and a set of key performance indicators are created to assess the resolution's effectiveness. The ABM method, contrary to other modeling approaches, is a fully customized method that can incorporate extensively various processes and elements. ABM applying the autonomous agent concept can integrate various components that exist in the complex supply chain and create a similar system to assess the supply chain efficiency.Tuotteiden kysyntä ohjaa erilaisia toimitusketju- ja logistiikkasijaintipäätöksiä, ja agenttipohjainen mallinnusmenetelmä (ABM) tuo innovatiivisia ratkaisuja toimitusketjun ja logistiikan ongelmien ratkaisemiseen. Tämä väitöskirja keskittyy agenttipohjaiseen mallinnusmenetelmään ja verkon optimointiin tällaisten ongelmien ratkaisemiseksi, ja sisältää kolme tapaustutkimusta, jotka voidaan luokitella kuuluvan yleisiin toimitusketjun hallinta- ja logistiikkaongelmiin. Ensimmäinen tapaustutkimus esittelee kuinka käyttämällä väestötiheyksiä Norjassa, Suomessa ja Ruotsissa voidaan määrittää strategioita jakelukeskusten (DC) sijaintiin käyttämällä matkan etäisyyden minimoimista. Kullekin skenaariolle kehitetään matka-aikakartat. Lisäksi analysoidaan näistä kolmesta maasta koostuvaa pohjoismaista aluetta ja esitetään viisi mahdollista sijaintia optimointituloksena. Toinen tapaustutkimus esittelee kuljetuskustannusmallintamisen prosessissa, jossa puutavaraa kerätään useilta alueilta ja kuljetetaan lähimpään keräyspisteeseen. Tämä tutkimusprojekti esittelee agenttipohjaista mallinnusta (ABM), joka yhdistää kattavasti noudon ja toimituksen toimitusketjumallin keskeiset elementit ja suunnittelee komponentit keskenään kommunikoiviksi autonomisiksi agenteiksi. Mallinnuksessa yhdistetään erilaisia komponentteja, kuten GIS-reititys, mahdolliset tilojen sijainnit, satunnaiset puunhakupaikat, kaluston mitoitus, matkan pituus sekä monimuotokuljetukset. ABM:n avulla mallinnetaan noutojen ja toimituksien koko ketju ja tuloksena saadaan aikasarjoja kuvaamaan käytössä olevat kuorma-autot, sekä varastomäärät ja ajetut matkat. Lisäksi arvioidaan erilaisia simuloinnin skenaarioita mahdollisten laitosten sijainnista ja kuorma-autojen lukumäärästä sekä tunnistetaan optimaalinen toimipisteen sijainti ja tarvittava autojen määrä. Kolmannessa tapaustutkimuksessa agenttipohjaista mallinnusstrategiaa käytetään ratkaisemaan ajoneuvojen aikataulujen ja kaluston optimoinnin ongelma. Ratkaisumenetelmää käytetään dataan, joka on peräisin todellisesta organisaatiosta, ja ratkaisun tehokkuuden arvioimiseksi luodaan lukuisia keskeisiä suorituskykyindikaattoreita. ABM-menetelmä, toisin kuin monet muut mallintamismenetelmät, on täysin räätälöitävissä oleva menetelmä, joka voi sisältää laajasti erilaisia prosesseja ja elementtejä. Autonomisia agentteja soveltava ABM voi integroida erilaisia komponentteja, jotka ovat olemassa monimutkaisessa toimitusketjussa ja luoda vastaavan järjestelmän toimitusketjun tehokkuuden arvioimiseksi yksityiskohtaisesti.fi=vertaisarvioitu|en=peerReviewed

    A Model for Accommodation Selection using GIS and Multi Criteria System

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    The main purpose of this research to develop a preference model for the best accommodation selection process in Chittagong city Bangladesh based on College Market Hospital and Park with GIS and Multi-Criteria System MCS A decision is the result of a comparison of one or more alternatives concerning one or more criteria that we considered relevant for the task at hand MCS is primarily concerned with how to combine the information from Multi- Criteria to form a single index of evaluation Multi-Criteria System MCS provides a more logical and scientific way for best accommodation selection MCS describes any structured approach used to determine overall preferences among alternative options where accomplish several criteria The results were having a sample of the computerized program that could be used to measure these indicators and their weights The integration of multi-criteria evaluation MCE and multi-criteria decision making MCDM techniques with the Geographical information system GIS are forward as providing the user with the means to evaluate various alternatives by multiple and collecting criteria These criteria are Market Office Rood Park Sea beach Hospital University College School Mosjid Mondir Temple Playground Airport and Police station There is a most important option is weight The weights for the multi-criteria system obtained from the multiple criteria For a selection of the best suitable location for accommodation there were a lot of elements that should take into some consideration The people who want to live in this location which provides their own facility in Chittagong city Bangladesh they can search their best accommodation by this work So people must save their time to get an appropriate location for this work So as a result the select a best accommodation considered by the multi-criteria The research work has been done based on some development area of Chittagong city in Banglades

    Prioritizing Offshore Vendor Selection Criteria for the North American Geospatial Industry

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    The U.S. market for geospatial services totaled US $2.2 billion in 2010, representing 50% of the global market. Data-processing firms subcontract labor-intensive portions of data services to offshore providers in South and East Asia and Eastern Europe. In general, half of all offshore contracts fail within the first 5 years because one or more parties consider the relationship unsuccessful. Despite the high failure rates, no study has examined the offshore vendor selection process in the geospatial industry. The purpose of this study was to determine the list of key offshore vendor selection criteria and the efficacy of the analytic hierarchy process (AHP) for ranking the criteria that North American geospatial companies consider in the offshore vendor selection process. After the selection of the initial list of factors from the literature and their validation in a pilot study, a final survey instrument was developed and administered to 15 subject matter experts (SMEs) in North America. The SMEs expressed their preferences for one criterion over another by pairwise comparisons, which served as input to the AHP procedure. The results showed that the quality of deliverables was the top ranked (out of 26) factors, instead of the price, which ranked third. Similarly, SMEs considered social and environmental consciousness on the vendor side as irrelevant. More importantly, the findings indicated that the structured AHP process provides a useful and effective methodology whose application may considerably improve the quality of the overall vendor selection process. Last, improved and stabilized business relationships leading to predictable budgets might catalyze social change, supporting stable employment. Consumers could benefit from derivative improvements in product quality and pricing

    Addressing decisions about new hospitals’ siting: a multidimensional evaluation approach

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    Background. Site selection for urban facilities is a crucial topic in planning decision processes for the several side effects they produce and the multiple criteria involved, especially for healthcare facilities. Nevertheless, the location problem has been ignored by most of the existing evaluation systems. Methods. Starting from a deep literature review and the analysis of hospitals in 10 European cities, the paper proposes an evaluation system divided into four macro-areas (Functional quality, Location quality, Environmental quality, Economical aspects), each in turn composed by criteria and sub-criteria. Results. The evaluation system has been applied for the site selection of “La Città della alute” in Milan, Italy. Furthermore, the ShOS (Selection hospitals’ Site) Evaluation Tool has been defined, with the aim of assessing the land suitability for new healthcare structures. Conclusion. The ShOS evaluation tool improves the transparency and robustness of the decision-making process and it could be broadly applied

    A multi-criteria decision making approach for the evaluation of roads and streets system in Gniezno

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    The article presents the application of the MCDM methods, belonging to the PROMETHEE family, for the evaluation of potential solutions of the road system (RS) in the selected area located in Gniezno, historical capital of Poland. The proposed set of heuristics variants of RS were assessed by a coherent family of criteria taking into account different groups of stakeholders. The decision problem was defined as an issue of prioritising a finite number of variants of road-rail system reconstruction. The proposed model of decision-maker’s preferences was developed based on the results of surveys conducted during public consultations with the residents of the area. The originality of the study consists in that the model became the basis for the final variants ranking that was subsequently compared with the results obtained using another MCDM method – ELECTRE III, where the decision-maker's preference model was developed on the basis of information obtained from independent experts

    Location of logistics hubs at national and subnational level with consideration of the structure of the location choice

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    International audienceThe location of logistic hubs is a strategic decision made after multicriteria analysis. This requires first the definition of quantitative or qualitative criteria that can be independent or partially conflicting. The decision of location can be made at different geographical levels (countries or regions). In this paper, we suggest a generic structuration of criteria by geographical level and by family for choosing hubs location, taking into account the involved structure of location choice, which is rarely done in the literature: sequential assessment (choice of a country, then of a region of this country) or simultaneous assessment (direct choice of a location among several regions belonging to different countries)

    INTEGRATION OF SCOR AND FUZZY AHP FOR LOCATION SELECTION OF EDIBLE WHITE COPRA AGRO-INDUSTRY

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    The selection of agro-industry location is essential in establishing, growing, and relocating agro-industrial systems for all forms of product development. In this regard, white copra has displayed a great economic potential due to export demand. To response this challenge, Indragiri Hilir Regency in Riau Province might become the most promising area since the location is lack of agroindustrial activity. Such condition leads to a excessive supply of coconut, which is in turn, causing the low price. This work aimed determine the best location for developing agroindustry for edible white copra based on multiple criteria. According to the findings, this research successfully created a new integration SCOR with Fuzzy AHP based on a multiple-criteria approach. At the first and second level, each option has equal rate of importance for each attribute and metric, while at the third level, corresponding to the highest importance, is the adaptability for increased shipping, procurement cost, days for coconut inventory, days for edible white copra stock. The fourth level, also corresponding to the highest importance, includes standard conformity, transportation facility, and the percentage of orders with the correct content. Based on the analysis, the locations showing the highest to the lowest importance were Tembilahan Hulu (0.194), Tempuling (0.152), Batang Tuaka (0.160), Kempas (0.118), Kuala Indragiri (0.100), Tembilahan (0.100), Teluk Belengkong (0.087), Pelangiran (0.080), and Enok (0.072). This research is expected to increase the development of edible white copra agroindustry in the Regency of Indragiri Hilir. Keywords: integration, SCOR, FUZZY AHP, multicriteria, edible white copr
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