Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM

Science Tools to Implement Ecosystem Based Management in Massachusetts (DRAFT)

In this report we provide a framework for implementing ecosystem based management (EBM) and suggest a range of science information tools and their appropriate application to the decision making process. These tools can be broadly classified as modeling tools, decision analysis tools, and indicators. Modeling tools allow the user to organize data, communicate scientific findings to management and stakeholder audiences, and test alternative management scenarios. When used unwisely, however, models can preclude options, present unusable scenarios, generate results in scales that differ from management needs, and impose huge time, data, and technical requirements (Manno et al., 2008). Decision analysis tools can inform management decisions but should not be relied upon solely; they are valuable aids in the process and provide opportunities for all-stakeholder input, visualization, and scenario analysis. Indicators are scientific measurements of ecological or socio-economic phenomena that provide data for monitoring and evaluating the systems being managed. While indicators are by and large widely accepted, their selection is based on expert opinion and involves a level of subjectivity. Inappropriately selected indicators can misinform management decisions. By helping to identify and mitigate lack of information, these science tools can be of great value in the shift to ecosystem based management

A new experience mining approach for improving low carbon city development

Developing low carbon city (LCC) has been widely appreciated as an important strategy for sustainable development. In line with this, an increasing number of cities globally have launched low carbon practices in recent years and gained various types of experience. However, it appears that existing studies do not present methods of how to use these valuable LCC experience in solving new problems. This study therefore introduces an experience mining approach to assist decision‐makers in reusing previous experience when tailoring LCC development strategies. The mining approach consists of three processes, namely, collecting historical cases which have been experiencing LCC, establishing LCC experience base, and mining similar experience cases. This study innovates the existing experience mining approach by introducing a two‐step mining process with considering the perspective of problem‐based urban characteristics (PBUCs) and the perspective of solution‐based urban characteristics (SBUCs). The application of the introduced mining approach has been demonstrated by a case study, where Shenyang’s energy structure is adopted as the target problem. The new experience mining approach provides a valuable reference for decision‐makers to retrieve similar cases for improving LCC development with the consideration of city characteristics.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156189/2/sd2046_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156189/1/sd2046.pd

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

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

Risks and Prospects of Smart Electric Grids Systems measured with Real Options

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Modelo de decisión para el diseño conceptual de un sistema de suministro sostenible de energía para la Sede Leticia de la Universidad Nacional de Colombia

ilustraciones, gráficas, tablasThe decentralized model of energy generation has emerged as a solution to provide electricity to isolated areas, ensuring energy security and increasing coverage. This model frequently leads to a dependency on a unique energy source; thus, it is necessary to change the paradigm of energy generation by adding other more sustainable sources. Unfortunately, there is not a well-defined route to establish which energy sources should be linked and in what way, making this restructuring a very complex problem involving a decision-making process. Generally, decisions are made only considering the economic or technical dimensions, ignoring the other dimensions such as environmental, social, and political, which could provide a more contextualized perspective. The aim of this study is to develop and test a methodology to find an optimal arrangement of energy sources in a decentralized electricity production model considering all sustainability dimensions. A methodology as the proposed in this work can support the stakeholders during the planning stages of energy supply systems. The methodology was applied to a specific case in Colombia, the campus Amazonia of the Universidad Nacional de Colombia, located in Leticia, a municipality where on-site generators are employed due to the difficulty of access. As a result, the proposed methodology generated nine different scenarios of energy arrangements according to an evaluation of energy sources using a sustainability approach that considered context aspects along with a carefully selected set of indicators and stakeholders' preferences.El modelo descentralizado de generación de energía surgió como una solución para el suministro de energía en áreas aisladas, asegurando la seguridad energética e incrementando la cobertura. No obstante, este modelo frecuentemente conlleva a una dependencia a una única fuente de energía, por lo que es necesario cambiar el paradigma de la generación de energía añadiendo otras fuentes más sostenibles. Desafortunadamente, no existe una ruta definida para establecer cuales fuentes de energía deben ser agregadas y de qué manera, convirtiendo esta reestructuración en un problema muy complejo que involucra la toma de decisiones. Generalmente, estas decisiones se toman considerando aspectos económicos o técnicos, dejando de lado otras dimensiones como la ambiental, social y política, que podrían proporcionar una perspectiva más contextualizada. El objetivo de este estudio es desarrollar y probar una metodología que permita encontrar un arreglo óptimo de fuentes de energía en un modelo de producción de electricidad descentralizado teniendo en cuenta todas las dimensiones de la sostenibilidad. La metodología propuesta en este trabajo puede ayudar a los principales involucrados durante las fases de planeación de sistemas de suministro de energía. Esta metodología fue aplicada a un caso específico en Colombia, la sede Amazonas de la Universidad Nacional de Colombia, ubicada en Leticia, un municipio donde generadores in situ son empleados debido al difícil acceso. Como resultado, la metodología propuesta generó nueve escenarios diferentes de arreglos energéticos de acuerdo a una evaluación de fuentes de energía en un enfoque de sostenibilidad considerando aspectos de contexto junto a una selección cuidadosa de indicadores y las preferencias de las partes interesadas. (Texto tomado de la fuente).Incluye anexosMaestríaBiorefinerías y biorefinació

Transdisciplinarity in energy retrofit: A conceptual framework

This study explores the role of Energy Retrofit (ER) in Low Carbon Transition (LCT). The literature recognises the need to move towards a transdisciplinary approach in ER, which encompasses multidisciplinarity and interdisciplinarity. However, the fragmentation between different disciplines remains a significant problem, mainly due to challenges associated with knowledge exchange across the allied disciplines that play a role in ER. The authors posit that ER projects has been conceptualised and implemented using a Systems perspective so that an integrated approach that is akin to transdisciplinarity could become commonplace. Against this background, the aim of this paper is to establish to what extent ER has been conceptualised as a System in the literature so that complexities can effectively be managed through a transdisciplinary approach. This work is based on a literature review of 136 peer-reviewed journal papers. The content analysis demonstrates that current research on transdisciplinarity in ER can be conceptualised in five categories and 15 lines of research. They are presented as a Conceptual Framework, which is this paper’s main contribution to existing knowledge. It reveals the direction of innovation in ER for LCT, and is illustrated as a cognitive map. This map exposes the current fragmentation implicit in the literature, and proposes critical connections that need to be established for a transdisciplinary approach. It also shows that the discourse on LCT changed by moving beyond the building scale; and recognising the need to embrace disruptive and local technologies, and integrating the social and technical aspects of ER. Innovative technical solutions and robust information modelling approaches emerge as key vehicles towards making decisions that pay regard to the economic, social and technical factors and that empower the prosumers to play an active role in LCT

Environmental Planning and Modeling

The focus of this reprint is on environmental planning and modeling. It examines articles on green consumption, biodiversity, and household waste recycling, as well as presenting a review of the trend in publications on household waste recycling. A number of country-based applications are presented and models are used to show how multiple perspectives can be considered in policy making. This reprint will be of special interest to researchers and readers involved in sustainability management. Further, although some chapters present models to solve sustainability problems, they also share policy and decision-making frameworks for applying such models

Land suitability analysis to assess the potential of public open spaces for urban agriculture activities

Dissertation submitted in partial fulfilment of the requirements for the degree of Master of Science in Geospatial TechnologiesIn a world increasingly dominated by cities and an accelerated urban sprawl, urban agriculture emerges as an alternative for the continuous stock and food supply that urban population demands. This thesis aimed to identify and evaluate potential available areas in public locations for implementing urban agriculture practices within the urban perimeter of the city of Bogota in Colombia. The methodology was conducted using variables reflecting the physical, environmental and socioeconomic components of the area. Two approaches were implemented to evaluate a land suitability analysis for urban agriculture to alleviate urban poverty by increasing food security and nutrition in the study area. The first approach was based on expert knowledge combining GIS with multicriteria decision making analysis (MCDM) using analytical hierarchical process (AHP) method, estimating that 21% of the study area presents highly suitability conditions for implementing urban agriculture activities. The second approach was developed using supervised machine learning algorithms for classification models based on historical data of the current sites, where urban agriculture activities were being implemented in the city, showing that 18% of the study area is in high suitability conditions for the implementation of urban agriculture activities. Both approaches indicated that the areas of excellent suitability are located in the South and Southwestern parts of the study area, emphasizing its congruence with the areas with the lowest socioeconomic levels in the city. It was found that approximately 2% of the study area has available spaces in public locations with a significant potential for urban agriculture practices. Three projected scenarios were simulated where 10%, 30% and in the most utopic case 50% of these spaces would be used for urban agriculture activities and the vegetable productivity in tons of five of the most popular crops grown was estimated