Bipolar method and its modifications

Over the past few decades, the strategies to perform energy systems analysis have evolved into multiple criteria-based frameworks. However, there still remains a lack of guidance on how to select the most suitable Multiple Criteria Decision Analysis (MCDA) method. These methods provide different decision recommendations for the Decision Makers, including ranking, sorting, choice, and clustering of the alternatives (e.g., technologies or scenarios) under evaluation. They deal with a variety of data typologies and preferences, and lead Decision Makers in shaping the energy systems of the future. Here, we evaluate the MCDA methods used in 56 case studies performing energy systems analysis at different scales. We find that close to 60% of these studies chose an MCDA method that was not the most adequate for the respective decision problem. In particular, this concerned the use of weighting methods (e.g., Analytical Hierarchy Process) in MCDA approaches not suited for this type of weights, sub-optimal selection of MCDA techniques for specific types of problem statements, and lack of handling rather evident interactions in preference models. Our analysis demonstrates that these deficiencies can be overcome by using a recently developed methodology and software that support Decision Makers and analysts in selecting the most suitable MCDA method for a given type of decision-making problem.

PurposeThis study aims to focus on the application of a multiple criteria decision analysis (MCDA) method to compare results presented by the Integrated Goals System based on the 12th edition of the Integrated Public Safety Areas (IPSAs) Award, which achieved goals established for Strategic Crime Indicators for the state of Rio de Janeiro, Brazil. The main objective of this research was to limit the compensatory effects of classification criteria on IPSAs that have achieved goals established for crime indicators by applying the MCDA method.Design/methodology/approachThe methodology was based on the application of MCDA. The MCDA method selected and used was ELECTRE III, being implemented by J-Electre software.FindingsCompared to results of the current method, the results of the ELECTRE III method showed a 94.87 per cent change in ranking positions revealed via the SIM method. This finding denotes the elimination of compensatory effects of the criteria. As a consequence, it can be affirmed that the application of resources by IPSA managers to reduce the prevalence of a single strategic crime indicator is no longer a success factor for awarding in the established goal system.Research limitations/implicationsAs limitations, it is possible to indicate the time cut used to carry out the research. The research may be extended to other issues of the productivity award.Practical implicationsThe methodology applied with the use of ELECTRE III revealed that the government could reduce the cost with the incentive program to reduce criminal indices.Social implicationsAs the MCDA method is based on a binary pairwise comparison system, the methodology imposes a change of attitude on local managers fighting crime to reduce crime indicators and to consequently build a local sense of safety in IPSAs.Originality/valueThis research fills a gap in the literature because there are few studies using the MCDA method in the field of public security. The value of the work lies in the creation of a method that gives the decision-maker, of the law enforcement agency, an alternative to improve the process of rewarding by productividad of the integrated areas of public security.

Royal Cosun, Avantium partner in biofuels, bioplastics process development

Multicriteria spatial decision support systems (MC-SDSS) have emerged as an integration of the geographical information systems (GIS) and multiple criteria decision analysis (MCDA) methods. GIS-based MCDA allows the incorporation of conflicting objectives and decision maker (DM) preferences into spatial decision models. During recent decades, a variety of research articles have been published regarding the implementation of methods and/or tools in a variety of real-world case studies. The article discusses, in detail, the criteria and methods that are implemented in GIS-based landfill siting suitability analysis and especially the exclusionary and non-exclusionary criteria that can be considered when selecting sites for municipal solid waste (MSW) landfills. This paper reviews 36 seminal articles in which the evaluation of candidate landfill sites is conducted using MCDA methods. After a brief description of the main components of a MC-SDSS and the applied decision rules, the review focuses on the criteria incorporated into the decision models. The review provides a comprehensive guide to the landfill siting analysis criteria, providing details regarding the utilization methods, their decision or exclusionary nature and their monotonicity.

This chapter analyzes the quality of XML learning object repositories. Special attention is paid to the models and methods to evaluate the quality of learning repositories. Multiple criteria decision analysis and optimization methods are explored to be applied for evaluating the quality of learning repositories. This chapter also presents the results of several large-scale projects co-funded by EU research programs that have been implemented in the area of learning repositories. Learning repositories’ technological quality model (system of criteria) and novel comprehensive model for evaluating the quality of user interfaces of learning repositories are presented in more detail. The general MCEQLS (Multiple Criteria Evaluation of Learning Software) approach is presented in this chapter. It is shown that the MCEQLS approach is suitable for evaluating the quality of learning repositories. The author believes that research results presented in the chapter will be useful for all educational stakeholder groups interested in developing learning repositories.

This paper considers the problem of sustainability assessment in urban and territorial planning projects using the Multi Attribute Value Theory (MAVT), a particular kind of Multiple Criteria Decision Analysis method. Starting from a real case concerning the transformation of an urban area in the city of Torino (Italy), the aim of the paper is to explore the contribution of MAVT for urban planning decision making processes. In the application, several alternative projects are evaluated on the basis of different criteria and attributes, such as availability of services, urban regeneration, acoustic emissions, land consumption and so on. In the result of this approach a ranking of sustainable alternative solutions is provided.

A novel multiple criteria decision analysis (MCDA) method is designed for comparing and ranking resolution solutions to a brownfield redevelopment project. In particular, an MCDA technique called the modified multilevel grey evaluation method is developed using concepts from grey systems theory, entropy and the analytical hierarchical process (AHP). To obtain weights for the range of criteria and sub-criteria used to assess and compare the resolution solutions, results obtained using AHP and an entropy technique are combined. In order to reflect uncertainty in the evaluation scores of the resolutions according to the sub-criteria, a grey systems class is employed to appropriately transform the scores. Subsequently, the evaluation method for the resolutions along with the combined weights is used to rank the resolutions. To demonstrate how this new methodology can be conveniently used in practice and provide valuable insights for aiding decision making, it is applied to a brownfield site in Xi'an, China, created by a former chemical factory.

The selection process of appropriate Performance Appraisal (PA) methods for organizations in today’s dynamic and agile environments along with its funding scales is a complex problem. Performance appraisal in modern organizations has become a part of the strategic approach toward integrating business policies and human resource activities. The existence of multiple criteria in the decision-making procedure makes finding the optimal PA method more challenging. The current study tackles a PA method assessment by applying a multiple criteria decision analysis method i.e., MULTIMOORA integrated Shannon’s entropy significance coefficient. A case study on the optimal PA method selection is analyzed by identifying the criteria and alternatives based on the literature and expert comments of the case-study employing two approaches, that is, MULTIMOORA and Entropy MULTIMOORA. The final rankings of the suggested methods are compared to TOPSIS and TOPSIS integrated Shannon’s entropy methods utilizing correlation coefficients of the final ranks. Eventually, by identifying the optimal PA approach i.e., 360-degree feedback, the selected optimal method employed in the case study and results are demonstrated and described with a comprehensive example.

Estimating the importance of consumer purchasing criteria in digital ecosystems

Energy security has become increasingly important because of its impact on all sectors of the economy, and even more because of the scarcity of primary energy resources and price fluctuations caused by geopolitical tensions. This has prompted all countries to assess their energy situation and take strategic measures to mitigate energy risks. Accordingly, the aim of this study is to identify the dimensions of energy security with the greatest impact on Morocco's energy security, as well as the priority strategic measures for mitigating energy risk. To this end, we consider the fuzzy analytic hierarchy process (F-AHP) method, which is a multiple criteria decision analysis method, which has been used to obtain results based on a structured evaluation process. The obtained results, following the considered comparison matrix, underscore that availability and resilience dimensions have the greatest impact on the Moroccan energy security, with respective weights of 48% and 28%. Besides, mitigating energy risk in Morocco primarily involves the development of renewable energies compared with seven other proposed measures, along with their degree of priority.

Multiple Criteria Decision Analysis (MCDA) is a subfield of Operational Research that aims to support Decision-Makers (DMs) in the decision-making process through mathematical models and computational procedures. In this perspective, MCDA employs structured and traceable protocols to identify potential actions and the criteria for evaluating them. MCDA procedures aim to define recommendations consistent with the preferences of DMs for the specific decision problem at hand. These problems are generally formulated in terms of either choosing the best action, classifying actions into pre-defined and ordered decision classes, or ranking actions from best to worst. As the evaluation criteria are generally conflicting, the main challenge is to aggregate them into a mathematical preference model representing the DM value system. We review the development of MCDA over the past fifty years and describe its evolution with examples of distinctive methods. They are distinguished by the type of preference information elicited by DMs, the type of the preference model (criteria aggregation), and the way of converting the preference relation induced by the preference model in the set of potential actions into a decision recommendation. We focus on MCDA methods with a finite set of actions. References to specific application areas will be given. In the conclusion section, some prospective avenues of research will be outlined.

The background to this research is that across the world there will be 200,000 tonnes of wind turbine blade waste to be disposed of each year from 2033. The purpose of the research is to compare the relative sustainability of alternative ways to deal with this waste, these being: landfill, incineration with heat recovery, co-processing in cement kilns, making furniture and bridge fabrication. The method is to use the UN Sustainable Development Goals (SDGs) to select 11 metrics for sustainability. The use of the SDGs adds to the objectivity of this process overcoming one of the principal weaknesses of Multiple Criteria Decision Analysis (MCDA). Quantitative information methods from Life Cycle Assessment, Geographic Information Science, census data and real options analysis of R&D, alongside qualitative information from Delphi studies and Strengths/Weaknesses/Opportunities/Threats analysis are combined in the assessment. Three MCDA methods are used, each calculates economic, social and environmental sustainability indices for the end-of-life alternatives which are then combined into integrated sustainability indices. A novel Delphi stopping condition based on consensus, consistency and convergence is used. The primary result is that bridge fabrication is the most sustainable alternative with furniture making in second place. Co-processing, incineration with heat recovery and landfill are progressively less sustainable alternatives. This result is robust to substantial changes in the selection of experts’ opinions, the weights for MCDA and the values of the metrics. These findings offer researchers and policymakers a robust decision making process, applicable to situations where choices are made on sustainability criteria.

<p><strong>Abstract</strong></p><p>The National Map of Saline – Alkaline Soils of Greece was recently developed within the initiative of the European Soil Partnership (ESP) of FAO. The technique combines between other MODIS satellite imagery, spatial interpolation methods and ground surveying to derive at 1 km spatial resolution maps of soil’s salinity (SS) and soil organic carbon (SOC).</p><p>The present study investigates for the first time the development of higher resolution maps of these soil properties adopting the aforementioned methodology. Furthermore, this study attempted to estimate the Carbon sequestration (SOC) using Remote Sensing and geostatistic methods of spatial analysis, a concern that is eminent today due to its effect on climate change mitigation.</p><p>As a case study the island of Mytilene in Greece is used, for which detailed information on soil properties as well as climatic, geomorphological, geological and soil data was available from previous studies. An MCDA (Multiple Criteria Decision Analysis) method was applied in a GIS environment using Landsat satellite imagery for the composition of a Saline - Alkaline map. Between the key soil parameters estimated spatially included the Electrical Conductivity (EC), Exchangeable Sodium Percentage (ESP) and pH. Geospatial data analysis methods were implemented to visualize all the derived parameters related for the study area and to analyze the final products in the spatial domain.</p><p>Finding suggests that climate change and soil directly affect one another. The impact of environmental and climate change in addition to unsustainable agricultural practices seems to be linked to salinity increase, soil erosion and loss of organic matter.  In addition, when land degradation as well as erosion and loss of vegetation occur, SOC emissions increase. Under these conditions, soil cannot absorb enough amounts of CO2, especially when soil salinization and sodicity exists; inputs are further limited due to declines in vegetation health. The role of geoinformation technologies in support of sustainable agricultural production under the pressure of both climate change and anthropogenic activities is also discussed within the present study framework.  </p><p><strong>KEYWORDS:</strong> geoinformation, soil, pH, salinity, soil organic carbon, geostatistics, earth observation, GIS, Greece</p>

“Although we know that it is not a familiar object, after a while we can say what it resembles”. The core task of an aerial image analyst is to recognize different object types based on certain clearly classified characteristics from aerial or satellite images. An interactive recognition assistance system compares selected features with a fixed set of reference objects (core data set). Therefore it is mainly designed to evaluate durable single objects like a specific type of ship or vehicle. Aerial image analysts on missions realized a changed warfare over the time. The task was not anymore to classify and thereby recognize a single durable object. The problem was that they had to classify strong variable objects and the reference set did not match anymore. In order to approach this new scope we introduce a concept to a further development of the interactive assistance system to be able to handle also short-lived, not clearly classifiable and strong variable objects like for example dhows. Dhows are the type of ships that are often used during pirate attacks at the coast of West Africa. Often these ships were build or extended by the pirates themselves. They follow no particular pattern as the standard construction of a merchant ship. In this work we differ between short-lived and durable objects. The interactive adaptable assistance system is supposed to assist image analysts with the classification of objects, which are new and not listed in the reference set of objects yet. The human interaction and perception is an important factor in order to realize this task and achieve the goal of recognition. Therefore we had to model the possibility to classify short-lived objects with appropriate procedures taking into consideration all aspects of short-lived objects. In this paper we will outline suitable measures and the possibilities to categorize short-lived objects via simple basic shapes as well as a temporary data storage concept for shortlived objects. The interactive adaptable approach offers the possibility to insert the data (objects) into the system directly and on-site. To mitigate the manipulation risk the entry of data (objects) into the main reference (core data) set is granted to a central authorized unit.

Tracking subset relations between the contents containers on the heap is fundamental to modeling the semantics of many common programing idioms such as applying a function to a subset of objects and maintaining multiple views of the same set of objects. We introduce a relation, must reference sets, which subsumes the concept of must-aliasing and enables existing shape analysis techniques to efficiently and accurately model many types of containment properties without the use of explicit quantification or specialized logics for containers/sets. We extend an existing shape analysis to model the concept of reference sets. Reference sets allow the analysis to efficiently track a number of important relations (must-=, and must-⊆) between objects that are the targets of sets of references (variables or pointers). We show that shape analysis augmented with reference set information is able to precisely model sharing for a range of data structures in real programs that cannot be expressed using simple must-alias information. In contrast to more expressive proposals based on logic languages (e.g., extensions of first-order predicate logic with transitive closure or the use of a decision procedure for sets), reference sets can be efficiently tracked in a shape analyzer.