Multiple Criteria Models Research Articles

A game theoretic decision-making approach to reduce mine closure risks throughout the mine-life cycle

ABSTRACT To align a post-mining site to the wants and needs of local communities and stakeholders, mine closure needs to consider criteria which may be difficult to value using conventional cost–benefit analysis. For example, criteria associated with the environment, socio-environmental relationships, health, and long-term sustainability. Game theory techniques are implemented to investigate how different stakeholder groups could act during mine closure planning and decision-making. Using game theory with sustainability criteria, this study proposes an innovative approach to analyze some key decisions throughout the mine life that affect closure. Non-cooperative game theory models are investigated by developing Nash equilibrium equations which are based on the change in environmental risk, economic potential, and impacts on company reputation. The modified equilibrium formulas can highlight the key sustainability criteria for multi-stakeholder closure planning and complex decision-making. The discussion explores how the developed model can assist mining stakeholders in understanding their position during the mine closure process. In all, the game theory and multiple criteria models can help structure and manage the complex closure risks throughout the mine life cycle.

Use of interval data envelopment analysis, goal programming and dynamic eco-efficiency assessment for sustainable supplier management

Two big challenges for sustainable supplier management consist of (1) properly integrating the multiple factors necessary to measure the sustainability performance of suppliers and (2) modeling the dynamic nature of those factors. In this study, we demonstrate the aggregation of environmental and economic supplier performance criteria into a single (eco-efficiency) index using Data Envelopment Analysis (DEA) for interval data. Suppliers are pre-qualified according to this index and are allocated orders using multiple criteria models for single and multiple sourcing. In multiple sourcing, preemptive, non-preemptive and fuzzy goal programming models are used with purchase price and eco-efficiency as conflicting objectives. Finally, eco-efficiency change is assessed using an approach based on the Malmquist productivity index, which monitors suppliers over time. Thus, our methodology can be used for supplier evaluation, selection and monitoring. Data obtained from an auto parts manufacturer is used to illustrate the proposed method.

An approach for hotel type selection based on the Single-Valued Intuitionistic Fuzzy Numbers

The main objective of this paper is to emphasize the importance of the involving the Multiple-Criteria Decision-Making (MCDM) methods in the process of the selection of the optimal type of hotel for investment. Besides, the application of the Single-Valued Intuitionistic Fuzzy Numbers (SVIFN) is proposed. The applicability of the proposed approach is demonstrated through real case study directed to the selection of the appropriate type of hotel for investment that should be constructed in the Golija Mountain. Three decision-makers estimated five alternative types of hotels relative to the five evaluation criteria. The obtained results are reliable and representative and confirm that introducing of the appropriate multiplecriteria models minimize the possibility of making wrong decisions.

An integration of theoretical knowledge, day by day experience and multicriteria methods to support the entrepreneurial learning process

PurposeThe purpose of this paper is to provide to the entrepreneurs, and propose to the scientific community, a newly structured knowledge system that includes the quality of customers and suppliers, to facilitate learning processes about the current state of the enterprise and new strategic approaches.Design/methodology/approachThe knowledge system is elaborated combining a long day-by-day experience in a specific Italian field [the independent after market (IAM)] with the theoretical knowledge of both economic and financial issues and multiple criteria (MC) methods of decision aid. The economic and financial key performance indicators are generatedad hocfor a specific sector and created with the concept that a company is in the center of a network composed of its suppliers, customers, competitors and the State. An MC model easily and consistently includes aspects that are different in terms of source and formal language. An MC method transparently synthesizes all these elements in relation to a specific decision problem. Integrating the potential of MC models and methods with economic and financial issues and context experience facilitates an effective knowledge transfer to the operators of the sector.FindingsThis methodology is oriented to the companies involved in the IAM and in particular to the manufacture, distributor and spare parts dealer categories (in Italy, almost 500 manufacturers, 150 distributors and 5,000 dealers). Manufacturers can use the methodology and its results to know the economic and financial performances of their customers, distributors can identify their strengths and weaknesses and the situation of their competitors and dealers can identify the most reliable future partners. Also, foreign manufacturers may be interested in this analysis, before selling in Italy, and banks and financiers could consult our knowledge frameworks to analyze the risk default.Originality/valueThe added value of this approach is to allow even small and medium enterprises, without an internal know-how for economic analyses, to use tools that clarify their relations with the interested parties of the macroeconomic system and facilitate the quality assessment of their portfolio of customers/suppliers.

Effect of settlement on nutrition and health status of pastoral Gabra women of reproductive age in Kalacha Location, Marsabit County, Kenya.

The objective of the present study was to evaluate the effect of settlement on the nutrition and health status of pastoral women of reproductive age. A cross-sectional survey that included a 24 h dietary recall was administered to 224 randomly selected Gabra women. Height and weight were used to compute BMI. Whole capillary blood was used to measure Hb. Additional capillary blood was collected on filter paper and dried blood spots were analysed for transferritin receptor, C-reactive protein and a1-acid glycoprotein. Descriptive statistics were used to analyse population characteristics. The t test and the x2 test were used to determine population differences. Multiple criteria models were used to determine the prevalence of Fe deficiency, anaemia and inflammation. Settled and semi-settled women in Kalacha Location in Marsabit County, Kenya. Non-pregnant women aged 15–49 years. Fe repletion was observed in 43% of settled and 40% of semi-settled women. Fe-deficiency erythropoiesis in was found in 18% of settled and 20% of semi-settled women, whereas 15% of settled compared with 25% of semi-settled women were suffering from Fe-deficiency anaemia. Anaemia due to chronic diseases was more prevalent in semi-settled women than in settled women, and more common than Fe-deficiency anaemia. Settled women were significantly less anaemic than semi-settled women, but had similarly high levels of chronic energy deficiency. While anaemia and Fe deficiency were more pronounced in semi-settled than settled women, anaemia of chronic disease and chronic infection were highly prevalent in both communities. Policies should be put in place to improve overall nutrition among pastoral women.

An objective approach to determining criteria weights

This paper presents an objective approach to determining criteria weights that can be successfully used in multiple criteria models. The methods of entropy, CRITIC and FANMA are presented in this paper as well as a possible combination of the methods of objective and subjective approaches. Although based on different theoretical settings, and therefore with different algorithms of realization, all methods have a decision matrix as a starting point. An objective approach to determining the weight of criteria eliminates the negative impacts of a decision maker on criteria weights as well as on the final solution of multicriteria problems. The main aim of this paper is to systematize description procedures as a kind of help when encountering a problem of determining the criteria weights for solving multicriteria tasks. A possibility of the method application is shown in a numerical example.

Multiple criteria districting problems

Districting problems are of high importance in many different fields. Multiple criteria models seem a more adequate representation of districting problems in real-world situations. Real-life decision situations are by their very nature multidimensional. This paper deals with the problem of partitioning a territory into “homogeneous” zones. Each zone is composed of a set of elementary territorial units. A district map is formed by partitioning the set of elementary units into connected zones without inclusions. When multiple criteria are considered, the problem of enumerating all the efficient solutions for such a model is known as being NP-hard, which is why we decided to avoid using exact methods to solve large-size instances. In this paper, we propose a new method to approximate the Pareto front based on an evolutionary algorithm with local search. The algorithm presents a new solution representation and the crossover/mutation operators. Its main features are the following: it deals with multiple criteria; it allows to solve large-size instances in a reasonable CPU time and generates high quality solutions. The algorithm was applied to a real-world problem, that of the Paris region public transportation. Results will be used for a discussion about the reform of its current pricing system.

Solving a multiobjective possibilistic problem through compromise programming

Real decision problems usually consider several objectives that have parameters which are often given by the decision maker in an imprecise way. It is possible to handle these kinds of problems through multiple criteria models in terms of possibility theory. Here we propose a method for solving these kinds of models through a fuzzy compromise programming approach. To formulate a fuzzy compromise programming problem from a possibilistic multiobjective linear programming problem the fuzzy ideal solution concept is introduced. This concept is based on soft preference and indifference relationships and on canonical representation of fuzzy numbers by means of their α-cuts. The accuracy between the ideal solution and the objective values is evaluated handling the fuzzy parameters through their expected intervals and a definition of discrepancy between intervals is introduced in our analysis.

Management of surgical waiting lists through a Possibilistic Linear Multiobjective Programming problem

This study attempts to apply a management science technique to improve the efficiency of Hospital Administration. We aim to design the performance of the surgical services at a Public Hospital that allows the Decision-Maker to plan surgical scheduling over one year in order to reduce waiting lists. Real decision problems usually involve several objectives that have parameters which are often given by the decision maker in an imprecise way. It is possible to handle these kinds of problems through multiple criteria models in terms of possibility theory. Here we apply a Possibilistic Linear Multiobjective Programming method, developed by the authors, for solving a hospital management problem using a Fuzzy Compromise Programming approach.

On models for the operation of a class of electronic marketplaces

Innovation in information technology and the use of the Internet have enabled electronic marketplaces to become an important mechanism for linking suppliers and customers in a cost-efficient fashion. Previous research has generally focused on the benefits of electronic marketplaces from transaction cost economics and strategic perspectives. Yet very little academic research has addressed how to actually operate such a marketplace. In this paper, after reviewing the status of electronic marketplaces research, we focus on an operational perspective. A model of an electronic marketplace linking customers and suppliers either directly or via an intermediary is given and solved under various scenarios. This model uses a single cost-minimizing objective and the extensions address issues such as (1) a physical presence for the electronic marketplace, which can provide value-added services and preserve anonymity; and (2) sole sourcing or dual sourcing. An additional model explicitly represents the diverse objectives of the multiple players in the market using goal programming. The contribution of this research to practitioners is to offer a cost-effective alternative to current forms of allocating supply and demand. The cost-minimizing and multiple criteria models and extensions in this study make a contribution to research by expanding the horizons of previous studies on the operation of electronic marketplaces.

Inequality measures and equitable approaches to location problems

Location problems can be considered as multiple criteria models where for each client (spatial unit) there is defined an individual objective function, which measures the effect of a location pattern with respect to the client satisfaction (e.g., it expresses the distance or travel time between the client and the assigned facility). This results in a multiple criteria model taking into account the entire distribution of individual effects (distances). Moreover, the model enables us to introduce the concept of equitable efficiency which links location problems with theories of inequality measurement. In this paper special attention is paid to solution concepts based on the bicriteria optimization of the mean distance and the absolute inequality measures. The restrictions for the trade-offs are identified which guarantee that the bicriteria approaches comply with the concept of equitable efficiency. These results are further generalized to bicriteria approaches not using directly the trade-off technique.

Bio-economic evaluation of dairy farm management scenarios using integrated simulation and multiple-criteria models

Appropriate selection of holistic management strategies for livestock farming systems requires: (1) understanding of the behaviour of, and interrelations between, the different parts of the system; (2) knowledge of the basic objectives of the decision maker managing such enterprise; and (3) understanding of the system as a whole in its agro-ecoregional context. A decision-support system based on simulation and mathematical programming techniques has been built to represent pastoral dairy production systems. The biological aspects (grass growth, grazing, digestion and metabolism, animal performance) are represented by simulation studies under a variety of management regimes. The outputs from the simulation runs (such as pasture utilisation, stocking rates, milk yields, fertilizer use, etc.) are used as data input to the multi-criteria decision-making models, and the latter have been used to select the management strategies which make the most efficient use of the farm's resources (i.e. land, animals, pastures). The paper discusses the effects and implications of different management scenarios and policies on the bio-economic performance of highland dairy farms in Costa Rica. Nevertheless, the model frameworks are generic and can be adapted to different farming systems or ruminant species. The effect of model formulation and sensitivity, different decision-maker objectives, and/or activity or constraint definitions on management strategy selection are also analysed.

The rôle of livestock in natural resources management

AbstractThis paper discusses some of the unique aspects of the interactions of livestock with the natural resources base. It argues the nature of these interactions make the use of a systems approach of particular importance when planning and executing livestock research if it is to be of any relevance to farmers in developing countries. The key issues are illustrated in two contrasting case studies.In Nepal, shifts in land use patterns have led to marked changes in the availability and use of fodder resources. Farmers indicate that they are no longer able to use these optimally. Fodder from at least 90 different types of tree (some of which have yet to be properly classified botanically) are used to supplement the diets of buffalo, cattle and goats during dry seasons when food is in short supply. The nutritive value of each of these is affected by a wide range of management and environmental factors. Furthermore, diet selectivity means that fractions consumed differ markedly amongst both tree species and classes of livestock. It is clearly not feasible for researchers to evaluate this diversity using existing in vitro or in vivo indicators of nutritive value. Initial studies suggest that this variability is implicitly catered for in farmers' own assessments of relative nutritive values. A mechanistic understanding of this indigenous technical knowledge and the development of appropriate techniques for integrating it with models of the biological responses of animals to nutrients might, therefore, allow more effective assessment of strategies for tree fodder utilization.Highland dairy systems in the humid tropics of Costa Rica (3000+ mm/year rainfall) could be very productive but suffer from a substantial dependence on imported inputs. Concentrate use is very high causing substantial underutilization of grazed pasture (the local resource), which is available year-round under these high-rainfall conditions. Over-supplementation with protein, which is the most expensive nutrient in the diet, at levels in excess of 200% of the requirement has been reported widely in these regions. Farmers want new strategies that enable them to manage their land and other resources in an alternative way, in order to be less dependent on grains and other imports. A decision-support system based on simulation and multiple criteria models representing a dairy farm has enabled the design and development of such strategies. Using this approach, farmers' objectives can be incorporated with a holistic understanding of the farming system in terms of management practices that will permit demand-driven animal production research at the farm level.

Dominance and potential optimality in multiple criteria decision analysis with imprecise information

This paper discusses multiple criteria models of decision analysis with finite sets of alternatives. A weighted sum of criteria is used to evaluate the performance of alternatives. Information about the weights is assumed to be in the form of arbitrary linear constraints. Conditions for checking dominance and potential optimality of decision alternatives are presented. In the case of testing potential optimality, the proposed appoach leads to the consideration of a couple of mutually dual linear programming problems. The analysis of these problems gives valuable information for the decision maker. In particular, if a decision alternative is not potentially optimal, then a mixed alternative dominating it is defined by a solution to one of the LP problems. This statement generalizes similar results known for some special cases. The interpretation of the mixed alternative is discussed and compared to its analogue in a data envelopment analysis context.

Patient satisfaction and normative decision theory.

This article explores the application of normative decision theory (NDT) to the challenge of facilitating and measuring patient satisfaction. Patient satisfaction is the appraisal, by an individual, of the extent to which the care provided has met that individual's expectations and preferences. Classic decision analysis provides a graphic and computational strategy to link patient preferences for outcomes to the treatment choices likely to produce the outcomes. Multiple criteria models enable the complex judgment task of measuring patient satisfaction to be decomposed into elemental factors that reflect patient preferences, thus facilitating evaluation of care in terms of factors relevant to the individual patient. Through the application of NDT models, it is possible to use patient preferences as a guide to the treatment planning and care monitoring process and to construct measures of patient satisfaction that are meaningful to the individual. Nursing informatics, with its foundations in both information management and decision sciences, provides the tools and data necessary to promote care provided in accord with patient preferences and to ensure appraisal of satisfaction that aptly captures the complex, multidimensional nature of patient preferences.

A multiple criteria decision-making approach to GIS-based land suitability evaluation

Abstract Land suitability evaluation in a raster GIS environment is conceptualized as a multiple-criteria decision-making (MCDM) problem. A combination of MCDM techniques selected for implementing the methodology included value and priority assessment techniques for scaling the interval and ordinal data respectively, and compromise programming (CP) to aggregate the unidimensional evaluations. The contribution of the proposed methodology to handle problems of scaling and dependence that often affect expert-based suitability analyses is discussed. A case-study of habitat evaluation for the endangered Mount Graham red squirrel is presented. The multiple-criteria models resulting from the CP analysis of an expert's perception of the habitat preference structure of the red squirrel are compared with data of actual habitat use. The predictive power of the models is good and sensitivity analysis based on the distance-metric parameter p of CP reveals some interesting differences between alternative strategies for data aggregation.

Decision-aid and decision-making

The objective of multiple criteria approaches is to help us to make better decisions, but what is the meaning of ‘better’? This field has developed considerably in the past twenty years. The development makes us fully aware of the limitations on objectivity encountered in the field of decision-aid and, consequently, of the virtual impossibility of providing a truly scientific foundation for an optimal decision. Work carried out under the rubric of mcdm ( multiple criteria decision making) bases its claims to legitimacy on a framework in which these limitations are left aside. multiple criteria decision aid ( mcda) must be seen from a different perspective. Its aim is, above all, to enable us to enhance the degree of conformity and coherence between the evolution of a decision-making process and the value systems and objectives of those involved in this process. The purpose of decision-aid is, therefore, to help us make our way in the presence of ambiguity, uncertainty and an abundance of bifurcations. We shall analyse multiple criteria concepts, models and procedures from both these viewpoints.

The evaluation of decision-aiding systems: Guidelines and methods

Few decision-aiding systems, such as Expert or Decision Support Systems, are formally evaluated. Yet when used to aid a decision making process, there is an assumption that an organization receives a return on the investment inherent in developing (or purchasing) and implementing the system. This return is generated by more effective, more efficient, or delegated (and hence cheaper) decision making. This paper considers the conceptual problems in evaluating decision-aiding systems. It proposes nine guidelines to which an evaluation method should adhere. Three general methods for evaluation are then discussed: control group experiments, attitude scales, and multiple-criteria models. Each is reviewed in the light of the conceptual requirements for evaluation, as represented by the nine guidelines. A general multiple-criteria method that fits the nine guidelines is then presented.

Modeling multiple criteria in the faculty assignment problem

This paper describes two multiple criteria models for generating teaching assignments for faculty members. The first model requires faculty members to input utility values for possible teaching schedules while the second model requires that each faculty member only rank order possible teaching schedules. Unlike previously proposed models for this problem, the models described in this paper allow the user to evaluate the impacts and tradeoffs between goals that are associated with each individual faculty member and goals that are associated with the organization as a whole during the faculty assignment process.

Selecting children for gifted classes: Choosing for breadth vs. choosing for depth

This article compares and contrasts two types of multiple criteria models that can be used to select children for gifted classes: breadth models and depth models. In a breadth model, children are selected for gifted classes if they score moderately well on several assessment areas simultaneously. In a depth model, children are selected for gifted classes if they score superlatively well on any one assessment area, regardless of the level of their performance in other assessment areas. In the study, three breadth models, three depth models, and a more traditional Intelligence Test Model were applied to a population of fourth graders (N = 159) in a small town. The results indicated that children selected by the breadth models had very high classroom grades and were well thought of by their teachers. However, depth models included more students with unusually high IQ scores and more promising underachievers than did breadth models. These and other factors made depth models more advantageous than breadth models.