Multi-criteria Ranking Research Articles

Multicriteria Prioritization and Partial Order in Environmental and Ecological Statistics

The complexity of the present data-centric world finds its expression in the increasing number of multi-indicator systems. This has led to the development of multicriteria ranking systems based on partial order. Partial order theory helps reveal why an object of interest holds a certain ranking position and how much it is subject to change if a composite indicator is upgraded. Partial order theory helps discover association and implication structures derived from formal concept lattices. Some innovative concepts, like relationships/ambiguity graphs are rendered. Examples are selected from live case studies of watersheds, biomanipulation and bridge network infrastructure.

Multicriteria prioritization and partial order in environmental sciences

The complexity of the present data-centric world finds its expression in the increasing number of multi-indicator systems. This has led to the development of multicriteria ranking systems based on partial orders. Order theory is a main pillar of structural mathematics. Partial orders help to reveal why an object of interest holds a certain ranking position and how much it is subject to change if a composite indicator is upgraded. Order theory helps to derive linear or weak orders without indicator weighting schemes. Hence, rankings obtained from decision support systems (DSS) which depend on many parameters beyond the data matrix can be checked and discrepancies can lead to examine the parameters of the DSS. Order theory helps discover association and implication structures derived from formal concept lattices. Association and implication networks among the attributes of the data matrix allow more insights into multi-indicator systems and lead to new hypotheses and motivate further research. Some new and innovative concepts, like separated subsets, antagonistic indicators, ranking stability fields are rendered. Separated subsets are the typical outcome of a partial order analysis; their identification leads to antagonistic indicators, which are responsible for the separatedness of object’s subsets. Numerical aggregation can be performed step-by-step and the question which values of a weight lead to an order inversion is of high interest. The concept of stability fields is one possible answer, discussed in this paper. After an outline of partial order theory some more specific theoretical results are shown, then we discuss the role of composite indicators in the light of partial order and give some examples of interesting applications of partial order. Finally examples are selected from real life case studies of watersheds, environmental performance evaluations, child well being, geographic and administrative regions and more.

A Mobile Service Recommendation System Using Multi-Criteria Ratings

With the rapid advancement of wireless technologies and mobile devices, mobile services offer great convenience and huge opportunities for service creation. However, information overload make service recommendation become a crucial issue in mobile services. Although traditional single-criteria recommendation systems have been successful in a number of personalization applications, obviously individual criterion cannot satisfy consumers’ demands. Relying on multi-criteria ratings, this paper presents a novel recommendation system using the multi-agent technology. In this system, the ratings with respect to the three criteria are aggregated into an overall service ranking list by a rank aggregation algorithm. Furthermore, all of the services are classified into several clusters to reduce information overload further. Finally, Based on multi-criteria rank aggregation, the prototype of a recommendation system is implemented. Successful applications of this recommendation system have demonstrated the efficiency of the proposed approach.

Multi-criteria decision-making in the selection of a renewable energy project in spain: The Vikor method

One of the characteristics of the Spanish energy system is its high degree of dependence on imports. In 2005, the Spanish government approved the new Renewable Energy Plan in the following sectors: Windpower, Hydroelectric, Solar Thermal, Solar Thermo-electric, Photovoltaic, Biomass, Biogas and Biofuels. The aim of the Plan is to make it possible to reach the target of 12% of primary energy being met from renewable sources by 2010. When selecting one from various Renewable Energy investment projects different groups of decision-makers become involved in the process. Decision-making has to take into consideration several conflicting objectives because of the increasingly complex social, economic, technological, and environmental factors that are present. Traditional single-criterion decision-making is no longer able to handle these problems. The Compromise Ranking method, also known as the VIKOR method, introduces the Multi-criteria ranking index based on the particular measure of “closeness” to the “ideal” solution. In this paper, we apply the method in the selection of a Renewable Energy project corresponding to the Renewable Energy Plan launched by the Spanish Government. The method is combined with the Analytical Hierarchy Process method for weighting the importance of the different criteria, which allows decision-makers to assign these values based on their preferences. The results show that the Biomass plant option (Co-combustion in a conventional power plant) is the best choice, followed by the Wind power and Solar Thermo-electric alternatives.

Deriving preference order of open pit mines equipment through MADM methods: Application of modified VIKOR method

In multiple attribute decision making (MADM) problem, a decision maker (DM) has to choose the best alternative that satisfies the evaluation criteria among a set of candidate solutions. It is generally hard to find an alternative that meets all the criteria simultaneously, so a good compromise solution is preferred. The VIKOR method was developed for multi-criteria optimization of complex systems. This method focuses on ranking and selecting from a set of alternatives in the presence of conflicting criteria. It introduces the multi-criteria ranking index based on the particular measure of “closeness” to the “ideal” solution. To deal with the uncertainty and vagueness from humans’ subjective perception and experience in decision process, this paper presents an evaluation model based on deterministic data, fuzzy numbers, interval numbers and linguistic terms. Combination of analytic hierarchy process (AHP) and entropy method was applied for attribute weighting in this proposed MADM method. To demonstrate the potential of the methodology, the proposed method is used for surface mine equipment selection problems.

Quantitative modelling of benchmarking process

In this paper, we consider the problem of establishing a quantitative model allowing, given a set of production units (enterprises, plants, banks, university departments, etc.), to determine those units that can be considered as benchmarks in terms of production efficiency and to evaluate for a unit, that is not a benchmark the gap that separates it from the benchmarks. A production unit is considered here as a transformation centre that consumes resources (input items) of different nature (information, human resources, energy, money, etc.) to deliver some products (output items) of different nature as well (manufactured products, services, information, energy, etc.). This benchmarking problem is, therefore, a multicriteria ranking problem that necessitates sensitivity analysis process to determine which items a given unit must improve in order to become as efficient as benchmark unit(s). We propose in this paper to formulate this problem using satisficing games, an evaluation method, that is, based on two measures namely selectability measure (that measures production level) and rejectability measure (that is, related to resources consumption) for each unit or alternative. Units for which the selectability measure exceeds the rejectability one will be considered as satisficing units and the benchmark units are those satisficing units that are not dominated.

Multi-criteria ranking of copper concentrates according to their quality – An element of environmental management in the vicinity of copper – Smelting complex in Bor, Serbia

The results of multi-criteria ranking of copper concentrates by their quality, according to their content of useful and harmful components, are presented in this paper. Cu, Ag and Au were taken as useful components, while Pb, Zn, As, Cd, Hg, Bi and Sb were considered as harmful with adequate weight parameters. Considering its specific role in copper metallurgy, sulfur in the concentrate was considered in two scenarios. In the first scenario S was considered as a useful and in the other one as a harmful component. The ranking is done by implementing the PROMETHEE/GAIA method with an additional implementation of the special PROMETHEE V method, using the standard limitations of the heavy metals content in the concentrate. In this way, it is possible to perform an optimization of the input charge for the copper extraction from two aspects. The first aspect covers benefits from the content of useful metals, while the second deals with the protection of the environment, considering the content of harmful components of the charge. Using multi-criteria decision making for the sake of ranking the quality of copper concentrates, as described in this paper, could be considered as a contribution to the methodology of forming the market price of this product.

Multi-criteria ranking and source apportionment of fine particulate matter in Brisbane, Australia

Environmental context. There are serious global concerns about the environmental and health effects of atmospheric air pollutants. However, estimates of pollutants from measurements made in the proximity of a source do not always represent the ultimate atmospheric concentrations. Therefore alternative methods of attributing pollutants to sources, and estimating their contributions to atmospheric concentrations, as demonstrated in the current work, will become an increasingly important area of environmental research. Abstract. This paper reports the application of multicriteria decision making techniques, Preference Ranking Organisation Methods for Enrichment Evaluation (PROMETHEE) and Graphical Analysis for Interactive Assistance (GAIA), and receptor models, principal component analysis/absolute principal component scores (PCA/APCS) and positive matrix factorisation (PMF), to data from an air monitoring site located on the campus of Queensland University of Technology in Brisbane, Australia and operated by Queensland Environmental Protection Agency (QEPA). The data consisted of the concentrations of 21 chemical species and meteorological data collected between 1995 and 2003. PROMETHEE/GAIA separated the samples into those collected when leaded and unleaded petrol were used to power vehicles in the region. The number and source profiles of the factors obtained from PCA/APCS and PMF analyses were compared. There are noticeable differences in the outcomes possibly because of the non-negative constraints imposed on the PMF analysis. Whereas PCA/APCS identified 6 sources, PMF reduced the data to 9 factors. Each factor had distinctive compositions that suggested that motor vehicle emissions, controlled burning of forests, secondary sulfate, sea salt and soil were the most important sources of fine particulate matter at the site. The most plausible locations of the sources were identified by combining the results obtained from the receptor models with meteorological data. The study demonstrated the potential benefits of combining results from multi-criteria decision making analysis with those from receptor models in order to gain insights into information that could enhance the development of air pollution control measures.

Combinatorial Systems Evolution: Example of Standard for Multimedia Information

The article addresses the issues of combinatorial evolution of standards in transmission of multimedia information including the following: (a) brief descriptions of basic combinatorial models as multicriteria ranking, knapsack-like problems, clustering, combinatorial synthesis, multistage design, (b) a description of standard series (MPEG) for video information processing and a structural (combinatorial) description of system changes for the standards, (c) a set of system change operations (including multi-attribute description of the operations and binary relations over the operations), (d) combinatorial models for the system changes, and (e) a multistage combinatorial scheme (heuristic) for the analysis of the system changes. Expert experience is used. Numerical examples illustrate the suggested problems, models, and procedures.

A multi-criteria ranking of different technologies for the anaerobic digestion for energy recovery of the organic fraction of municipal solid wastes

This paper describes a conceptual framework and methodological tool developed for the evaluation of different anaerobic digestion technologies suitable for treating the organic fraction of municipal solid waste, by introducing the multi-criteria decision support method Electre III and demonstrating its related applicability via a test application. Several anaerobic digestion technologies have been proposed over the last years; when compared to biogas recovery from landfills, their advantage is the stability in biogas production and the stabilization of waste prior to final disposal. Anaerobic digestion technologies also show great adaptability to a broad spectrum of different input material beside the organic fraction of municipal solid waste (e.g. agricultural and animal wastes, sewage sludge) and can also be used in remote and isolated communities, either stand-alone or in conjunction to other renewable energy sources. Main driver for this work was the preliminary screening of such methods for potential application in Hellenic islands in the municipal solid waste management sector. Anaerobic digestion technologies follow different approaches to the anaerobic digestion process and also can include production of compost. In the presented multi-criteria analysis exercise, Electre III is implemented for comparing and ranking 5 selected alternative anaerobic digestion technologies. The results of a performed sensitivity analysis are then discussed. In conclusion, the performed multi-criteria approach was found to be a practical and feasible method for the integrated assessment and ranking of anaerobic digestion technologies by also considering different viewpoints and other uncertainties of the decision-making process.

Physical damage to coastal dunes and ecological impacts caused by vehicle tracks associated with beach camping on sandy shores: a case study from Fraser Island, Australia

As coastal populations expand, demands for recreational opportunities on beaches and coastal dunes grow correspondingly. Although dunes are known to be sensitive to direct human disturbance and provide irreplaceable ecosystem services (e.g. erosion control, critical habitat and nesting sites), dunes serve as campsites for large numbers of people (∼90,000 p.a.) on the ocean-exposed shores of Fraser Island, Australia. Campsites are located in the established dunes and can only be accessed with 4WD vehicles along tracks cut directly from the beach through the foredunes. Here we quantified the extent of physical damage to foredunes caused by this practice, and tested whether human-induced physical changes to foredunes translate into biological effects. Of the 124 km of ocean-exposed beaches, 122 km (98%) are open to vehicles driven on the beaches, and camping zones cover 28.7 km or 23% of the dunes. A total of 235 vehicle tracks are cut across the foredunes at an average density of eight tracks per km of beach. These tracks have effectively destroyed one-fifth (20.2%) of the dune front in camping zones, deeply incising the dune-beach interface. There is evidence of accelerated erosion and shoreline retreat centred around vehicle tracks, resulting in a “scalloping” of the shoreline. No dune vegetation remains in the tracks and the abundance of ghost crabs (Ocypode spp.) is significantly reduced compared with the abutting dunes. Because current levels of environmental change caused by dune camping may not be compatible with the sustainable use of coastal resources and conservation obligations for the island (listed as a World Heritage Area and gazetted as a National Park), restoration and mitigation interventions are critical. These will require spatial prioritisation of effort, and we present a multi-criteria ranking method, based on quantitative measures of environmental damage and ecological attributes, to objectively target rehabilitation and conservation measures. Ultimately, coastal management needs to develop and implement strategies that reconcile demands for human recreation, including beach camping, with conservation of coastal dune ecosystems.

Extension of VIKOR method for decision making problem with interval numbers

The VIKOR method was developed for multi-criteria optimization of complex systems. It determines the compromise ranking list and the compromise solution obtained with the initial (given) weights. This method focuses on ranking and selecting from a set of alternatives in the presence of conflicting criteria. It introduces the multi-criteria ranking index based on the particular measure of “closeness” to the “ideal” solution. The aim of this paper is to extend the VIKOR method for decision making problems with interval number. The extended VIKOR method’s ranking is obtained through comparison of interval numbers and for doing the comparisons between intervals, we introduce α as optimism level of decision maker. Finally, a numerical example illustrates and clarifies the main results developed in this paper.

Mine design selection under uncertainty

Frequently, alternative technically feasible mine designs and production scenarios are available for decision makers to consider. The selection of a mine design is then based on estimating net present values of all possible, technically feasible mine plans so as to select the one with the maximum value. Conventional risk and sensitivity analysis are also performed as decision supporting tools. Given the multiple market and geological uncertainties associated with mining investments, as well as the management flexibility to respond to new future information, the sufficiency of conventional economic analysis tools based on the static discounted cash flow analysis may be questionable. This paper proposes a multicriteria ranking system for selection between alternative mine designs under uncertainty. The system is based on integrating multiple market and geological uncertainties as well as the operating flexibility to revise the ultimate pit limits using a Monte Carlo based real options valuation (ROV) model. To compare the methods, the article applies the proposed system, along with other three ranking methods, to rank possible mine designs for a copper and a gold mine. It has been found that, in addition to the higher value of the mine design selected by the proposed system, its average mis-ranking is significantly lower than the other three ranking methods. For the copper mine, a reduction in the average mis-ranking of 37–58% could be achieved when using the proposed ranking system, while for the gold mine case, a higher reduction of 51–64% in the average mis-ranking is obtained.

An approach to multicriteria decision-making based on interval-valued intuitive fuzzy set with incomplete information

A multicriteria ranking method was proposed in which the information on the criteria's weights was incomplete and the criteria's value was interval intuitive fuzzy set.The interval-valued intuitive fuzzy set of each program was aggregated through logical algorithms.The Hamming distance of each program was computed and nonlinear programming model was established.By using particle swarm optimization algorithms,the optional criteria weights were gained.And ranking was performed through the comparison of the distances between interval-valued intuitive fuzzy set and superior program inferior program alternative.Eventually,a practical example was provided to illustrate the validity and feasibility of this method.

The Nakamura numbers for computable simple games

The Nakamura number of a simple game plays a critical role in preference aggregation (or multi-criterion ranking): the number of alternatives that the players can always deal with rationally is less than this number. We comprehensively study the restrictions that various properties for a simple game impose on its Nakamura number. We find that a computable game has a finite Nakamura number greater than three only if it is proper, nonstrong, and nonweak, regardless of whether it is monotonic or whether it has a finite carrier. The lack of strongness often results in alternatives that cannot be strictly ranked.

Multicriteria ranking of segments of urban engineering service networks by contradictory data using the delphi method and multiset theory

This paper considers the problem of multicriteria ranking of segments of urban engineering service networks by a group of experts in remedial maintenance scheduling. A multiset theory approach is used that allows for all (including contradictory) expert estimates. The individual estimates for segments of urban engineering service networks with respect to special criteria and the estimates for criteria are determined by the pairwise comparison method, based on Saaty’s scale, while the resulting fuzzy solutions are obtained using the Bellman-Zadeh approach.

Impact of the degree of a company’s success on the importance of the criteria for selecting a new product

The paper consists of two parts. The first part presents a new research methodology of a complex problem in business decision-making: determining the relative importance of the criteria for selecting a new product. This methodology facilitates providing recommendations for defining the relative importance of criteria and subcriteria for selecting a new product depending on the present situation in the company selecting a new product and its setting. In this manner is determined mutual dependence of the relative importance of criteria for selecting a new product on the company’s degree of success. For this reason, the whole procedure has a dynamic character, and it can be applied to various situations and at different moments of observation. Recommendations provided in this way represent the input data and support for subsequent multicriteria ranking of the alternatives for a new product.

A Multi-Criteria Analysis of Spelt Food Processing Alternatives on Small Organic Farms

ABSTRACT The nutritional, technological and processing characteristics of spelt wheat make it suitable for organic farming. Furthermore, spelt wheat can be directly processed into different kinds of food products on the farm itself, and represents additional business and market opportunities for organic farmers. In this paper we examine different spelt processing alternatives on a chosen organic farm in northeastern Slovenia. Simulation modeling, cost-benefit analysis and multi-criteria decision analysis were applied in order to find the most suitable spelt processing solution for the analyzed farm. The presented methodological framework upgrades the standard financial cost-benefit analysis with a quantitative utility function and a qualitative DEX-i modeling approach. The calculation of utility function (u) and DEX-i evaluation produced the following spelt processing project rankings: spelt husking (u = 2,67) spelt cookies (u = 2,18), spelt flour (u = 1,65) and spelt bread (u = 1,63). The proposed methodology enables multi-criteria spelt processing project ranking; however, further studies are suggested for the development of multi-criteria decision analysis-based methods for this topic.

Single and Multi-Criteria Ranking of Mutual Fund Schemes

We evaluate the performance of 21 equity (growth) funds using data envelopment analysis (DEA), Semi-Standard Deviation, Negative Potential Measure, and Morning Star Methodology. The results are compared with those obtained using conventional performance evaluation methods of Sharpe, Treynor, and Jensen. DEA is a multi input-output analytical tool, which includes transaction costs, diversification efficiency, and fund manager's stock selection skills in addition to risk and return. Semi-standard deviation and Negative Potential are modified risk measures which reflect a fund's downside risk only. We use two evaluation windows of 1997 - 2000 and 2001 - 2004 to analyze rank migration, and 5 investment horizons of 1, 3, 6, 12 and 24 months to include preferences of different investors.

Improving Text Categorization by Multicriteria Feature Selection

Text categorization involves assigning a natural language document to one or more predefined classes. One of the most interesting issues is feature selection. We propose an approach using multicriteria ranking of eatures, a new procedure for feature selection, and apply these to text categorization. Experimental results dealing with Reuters-21578 and 20Newsgroups benchmark data and the naive Bayes algorithm show that our proposal outperforms conventional feature selection in text categorization performance.