Stochastic Multicriteria Acceptability Analysis Method Research Articles

Consensus reaching in multi-criteria social network group decision making: A stochastic multicriteria acceptability analysis-based method

Multi-criteria social network group decision making (SNGDM) that allows decision makers (DMs) to interact with each other has attracted increasing attention in the field of decision analysis. In this paper, we take stochastic multicriteria acceptability analysis (SMAA) into account to study consensus reaching processes in multi-criteria SNGDM problems with manipulative behaviors. First, we propose a SMAA-based method to transform decision matrices into fuzzy preference relations to detect manipulators in multi-criteria SNGDM. Then, we design a new consensus determining mechanism using the weight stability interval and SMAA methods, which does not require a consensus threshold to be determined in advance. Based on this, we propose a two-stage feedback process to help DMs reach consensus. Then, we propose an algorithm to summarize the main steps of the proposed method. Finally, we use a case study of nursing home location selection to illustrate the effectiveness of the proposed method.

Consensus-based failure mode and effect analysis in group decision-making with incomplete weights of risk factors: Case study of stereotactic body radiation therapy for lung cancer

Failure mode and effect analysis (FMEA) is a widely used management technique to identify potential failure modes in products, processes, systems, and services to assign limited resources for implementing improvement efforts. For the FMEA with a number of experts, the experts may take different influences on the decision-making process due to the difference between individual rationality and cognition and the influence of social relations. Besides, incomplete weights of risk factors are vital to capturing the fuzziness of experts’ evaluation. Therefore, this paper proposes a consensus-based FMEA method to explore that how cooperative relationship network of experts, the consensus process, and incomplete weight information of risk factors in FMEA influence the decision-making process. First, a consensus reaching process considering cooperative relationships between experts, the self-confidence of experts, and minimum adjustment of expert opinion is proposed to derive a collective evaluation of group. Afterward, the stochastic multicriteria acceptability analysis method is integrated with the gained and lost dominance score method to deal with incomplete weights of risk factors in the FMEA. The proposed method is employed in a case study about ranking the failure modes of stereotactic body radiation therapy for lung cancer patients. The robustness and feasibility of the proposed method are validated by comparative analysis.

Numerical Calculation Method of Target Damage Effectiveness Evaluation under Uncertain Information of Warhead Fragments

In order to scientifically evaluate the target damage effectiveness when warhead fragments formed by projectile explosion attack targets, this paper proposes a new method by using the multi-layer warhead fragments distribution division mechanism to study an evaluation and calculation model of target damage effectiveness under uncertain information of warhead fragments. On the basis of the spatial relationship between projectile explosion position and target, we first analyze the target damage rules based on the target’s own vulnerability characteristics. Then we use the fuzzy prior probability theory to establish the membership function of the target damage factor and an evaluation model of the target damage grade, and use the stochastic multi-criteria acceptability analysis method to obtain the evaluation index value of the target damage level. Finally, considering the ratio between the effective area of the warhead fragment group attacking target and the area of target itself and the effective number and area ratio of warhead fragments penetrating target, we give a numerical calculation method of target damage effectiveness. Through simulation and calculation, the results show that when the distance between the projectile explosion position and the target is less than 7 m and the coordinate interval of the projectile flight direction is −2.5 m to 2.5 m, the damage probability of warhead fragments to the target is greater than 75%. When the weight of the damage factor of the target changes, the damage effectiveness of the target also changes, and this result is in accordance with the actual experiment, which verifies the rationality of the proposed mathematical model.

Compromise solutions for stochastic multicriteria acceptability analysis with uncertain preferences and nonmonotonic criteria

AbstractAs one of the most popular multiple criteria decision‐making (MCDM) methods, the stochastic multicriteria acceptability analysis (SMAA) is powerful in dealing with the uncertain preference information of decision makers. However, how to find compromise solutions for MCDM problems remains an open question in the SMAA family. A compromise solution refers to an alternative that is the closest to the ideal solution. In this paper, we propose an improved SMAA method, called the SMAA with compromise solutions (SMAA‐CO), to determine compromise solutions for MCDM problems with the uncertain preferences of decision makers and conflicting criteria. The SMAA‐CO uses nonmonotonic additive value functions to depict decision makers’ ideal values for reference points. We apply the proposed method to capture multiple decision makers’ uncertain preference information. An illustrative example concerning supplier selection in the pulp and paper industry is used to show the applicability of the proposed method. Some managerial insights are given.

Measuring Olympics Achievements via Stochastic Multicriteria Acceptability Analysis

The lexicographic and sum ranking systems are two widely-used instruments to measure Olympics achievements. However, the lexicographic ranking system is typically criticized as overvaluing gold medals, while the sum ranking system is particularly criticized as devaluing gold medals and incapable of discriminating National Olympic Committees (NOCs) with identical total number of medals. Meanwhile, there are controversial scoring schemes to assign points to gold, silver and bronze medals. In addition, measuring Olympics achievements in either the Winter or the Summer Olympic Games is unfair to the NOCs who perform significantly different at both Olympics. These issues are addressed in this study by developing a sophisticated mathematical transformation without the exact weights determination to aggregate the lexicographic ranking system in an interval metric. An interval decision matrix is therefore formulated under the simultaneous consideration of the Winter and the Summer Olympics. A Stochastic multicriteria acceptability analysis method is finally utilized to provide a robust measurement with sufficient discriminating power. Spearman’s rank correlation coefficients are calculated to indicate the merits of our method. The proposed method and relative analysis are demonstrated using the date drawn from the Sochi 2014 Winter Olympics and the Rio 2016 Summer Olympics.

On generating utility functions in Stochastic Multicriteria Acceptability Analysis

Stochastic Multicriteria Acceptability Analysis (SMAA) has become a popular Multi-Criteria Decision Aiding tool when some parameters of the decision problem are uncertain or have not been set. SMAA methods use Monte-Carlo simulation of the uncertain values to obtain indicators that inform decision making. While there is considerable literature on sampling of attribute weights, the problem of generating utility values is addressed less frequently. In this paper, we show that direct assignment of random utility values can lead to a biased sample of utility functions. We then introduce new methods to avoid this bias and discuss desirable properties for generating such utility functions. Then, we present a computational study to compare the different methods with regards to the desired properties, concluding that the new approaches perform much better. We also show how these techniques can be extended to consider only utility functions of a specific shape such as concave, convex or s-shaped. Besides SMAA multi-criteria analyses, the techniques studied in this paper can also be used in other contexts, e.g., decision trees and game theory, whenever utility functions need to be simulated to inform decision makers or to study the behavior of different methods.

SMAA methods and their applications: a literature review and future research directions

Stochastic multicriteria acceptability analysis (SMAA) is a family of multiple criteria decision making (MCDM) methods dealing with incomplete, imprecise, and uncertain information on the evaluations and preference model parameters. As it provides a general framework that has extensions to deal with various specificities in MCDM problems, the development of SMAA methods and their applications in real-life decision-making problems have been increased over the recent years. This paper provides an up-to-date literature review of different SMAA methods and their applications in various areas. First, we selected, from different on-line data base, 118 articles published between 1998 and 2017. We categorized the selected papers into theoretical and applied. While the theoretical papers were analyzed based on the method’s aggregation procedure, type of problem, type of method’s outputs and inputs, the applied papers were separated and analyzed by application areas. Then, we provide some descriptive statistics, analyzing the papers regarding to publication year and journals of publication. Finally, we provide some guidelines to assist decision-makers in the choice of a SMAA method on a specific decision-making context and some future research directions.

Multicriteria evaluation of carbon-neutral heat-only production technologies for district heating

Climate change mitigation requires reducing dependence on fossil fuels and transition to low carbon energy production technologies. Nearly half of the global final energy consumption is thermal energy produced from technologies with high carbon dioxide emission. As such, it is imperative to employ carbon-neutral heat production to achieve a sustainable energy system.This paper presents a real-life case of applying multicriteria decision analysis for evaluating carbon-neutral heat-only production technologies in a major district heating system in Finland. A group of 10 experts from the energy company contributed in defining the alternative technologies and multiple economic, technological, and environmental evaluation criteria. The experts also provided the criteria measurements and preference information for different criteria. The alternatives were compared using Stochastic Multicriteria Acceptability Analysis (SMAA). SMAA is a simulation based method for decision problems where different kind of uncertain information is represented by probability distributions. Because the preferences of the experts were highly conflicting, the SMAA method was extended within this study to treat conflicting preferences.The most preferred alternatives were short-term heat storages and electric boilers based on renewable power. These alternatives may be considered attractive future solutions particularly in balancing peak load heat consumption and production.

STOCHASTIC MULTICRITERIA ACCEPTABILITY BASED ROUTING TECHNIQUE FOR AD HOC NETWORK

Device to device Communication is a very impressive method of communication as it does not need any pre exiting expensive communication infrastructure. Devices (nodes) themselves perform all the network operations such as routing. Such types of networks are very useful in areas where communication infrastructure is not available or it was destroyed by some kind of mistake. A mobile Ad-hoc network is a network of this class. In a MANET routing is done by nodes themselves and there are several methods available in the literature of routing. Reactive routing is a technique in which routes are recorded only if they are needed. AODV is most popular reactive routing protocol of mobile ad hoc network. In this paper we are presenting a novel concept of route selection “SMART” in which stochastic multi-criteria acceptability analysis method is used to find the best route for transmission of packet from source to destination. This acceptability method is a branch of multi-criteria decision method (MCDM), and it has flexibility to assign importance to different criteria and the same can be change according to the situation in which the network is being used. The proposed scheme is implemented on NS-2 Platform and compared with other noteworthy research papers for verification of improvement in performance.

A Quantitative Approach for Benefit-Risk Assessment Using Stochastic Multi-Criteria Discriminatory Method

ABSTRACTBenefit-risk (BR) assessment is important to ensure safety and effectiveness of medical projects in clinical development and post marketing surveillance. The evaluation of the balance between benefits and risks of a drug is fundamental to all stakeholders involved in the development, registration, and use of drugs. Many quantitative approaches have been developed that may draw together data from different sources to present them in ways that can aid decision-making. Among these quantitative approaches, multicriteria decision analysis (MCDA) is one of the most useful approaches, since it provides a framework for systematic and replicable analyses of complex decision problems involving value tradeoffs. In most real-life situations, decision makers are not able to get exact preference information (weights). To overcome this limitation of MCDA, a method called stochastic multicriteria acceptability analysis (SMAA) was proposed as a quantitative approach to BR assessment in drug development. The chief advantage of SMAA over most other MCDA methodologies is that it can be used with limited or no preference information and a data-driven approach can be used to obtain the inherent weighting among multicriteria. In this article, we propose the stochastic multicriteria discriminatory method (SMDM) that is based on the SMAA method with a focus on providing straightforward and informative assistance to decision making. We use SMDM to derive probability of better treatment, probability of significantly better treatment and the expected p-values of the evaluation results, on the basis of limited partial weight information or no weight information at all.

Multicriteria evaluation of heating choices for a new sustainable residential area

The city of Loviisa in Finland is planning a new sustainable residential area with a total of 240,000m2 of residential houses and apartment buildings with services. The city wants to promote sustainable energy solutions in the area, considering various renewable energy forms for heating. The aim of this research is to evaluate which heating system would be best for a new single-family house when different technical, economic, environmental and usability criteria are considered. A group of experts evaluated the alternative heating systems with respect to the criteria. The citizens were involved with a questionnaire to provide preference information for different criteria. Altogether 11 alternative heating systems were evaluated in terms of 15 criteria. The Stochastic Multicriteria Acceptability Analysis (SMAA) method was used to analyze this problem. The SMAA method was extended to handle a hierarchy of criteria and sub-criteria. The problem was analyzed in two phases based on expert evaluation for the criteria measurements first without the preference information from citizens and after this with the information. The results show that district heating produced by biomass based CHP is the most widely acceptable heating alternative followed by ground source heat pump both without and with preference information.

Using stochastic multi-criteria acceptability analysis methods in SEA: an application to the Park of Trasimeno (Italy)

Strategic Environmental Assessment is an important tool, one that has been compulsory in the European Union since 2004. The procedure enables the inclusion of the environment in the planning phase to avoid environmental problems in the future. The individuation and valuation of reasonable alternatives is one of the most important aspects introduced by the Directive. Multi-criteria Decision Analysis can be a tool for choosing the best reasonable alternative. In this study, we test the use of Stochastic Multi-criteria Acceptability Analysis, which is a new family of multi-criteria methods. In particular, we use the SMAA-2 method, which allows the use of cardinal data and does not require information on Decision Makers’ preferences. In this application, SMAA-2 enables a solution for a Management Plan of Trasimeno Park in a very sensitive political and social context.

Prospect theory and stochastic multicriteria acceptability analysis (SMAA)

We consider problems where multiple decision makers (DMs) want to choose their most preferred alternative from a finite set based on multiple criteria. Several approaches to support DMs in such problems have been suggested. Prospect theory has appealed to researchers through its descriptive power, but rare attempts have been made to apply it to support multicriteria decision making. The basic idea of prospect theory is that alternatives are evaluated by a difference function in terms of gains and losses with respect to a reference point. The function is suggested to be concave for gains and convex for losses and steeper for losses than for gains. Stochastic multicriteria acceptability analysis (SMAA) is a family of multicriteria decision support methods that allows representing inaccurate, uncertain, or partly missing information about criteria measurements and preferences through probability distributions. SMAA methods are based on exploring the weight and criteria measurement spaces in order to describe weights that would result in a certain rank for an alternative. This paper introduces the SMAA-P method that combines the piecewise linear difference functions of prospect theory with SMAA. SMAA-P computes indices that measure how widely acceptable different alternatives are with assumed behavior. SMAA-P can be used in decision problems, where the DMs’ preferences (weights, reference points and coefficients of loss aversion) are difficult to assess accurately. SMAA-P can also be used to measure how robust a decision problem is with respect to preference information. We demonstrate the method by reanalyzing a past real-life example.

Multivariate Gaussian criteria in SMAA

We consider stochastic multicriteria decision-making problems with multiple decision makers. In such problems, the uncertainty or inaccuracy of the criteria measurements and the partial or missing preference information can be represented through probability distributions. In many real-life problems the uncertainties of criteria measurements may be dependent. However, it is often difficult to quantify these dependencies. Also, most of the existing methods are unable to handle such dependency information. In this paper, we develop a method for handling dependent uncertainties in stochastic multicriteria group decision-making problems. We measure the criteria, their uncertainties and dependencies using a stochastic simulation model. The model is based on decision variables and stochastic parameters with given distributions. Based on the simulation results, we determine for the criteria measurements a joint probability distribution that quantifies the uncertainties and their dependencies. We then use the SMAA-2 stochastic multicriteria acceptability analysis method for comparing the alternatives based on the criteria distributions. We demonstrate the use of the method in the context of a strategic decision support model for a retailer operating in the liberated European electricity market.

Pseudo-criteria versus linear utility function in stochastic multi-criteria acceptability analysis

Stochastic multi-criteria acceptability analysis (SMAA) is a multi-criteria decision support method for multiple decision-makers (DMs) in discrete problems. SMAA does not require explicit or implicit preference information from the DMs. Instead, the method is based on exploring the weight space in order to describe the valuations that would make each alternative the preferred one. Partial preference information can be represented in the weight space analysis through weight distributions. In this paper we compare two variants of the SMAA method using randomly generated test problems with 2–12 criteria and 4–12 alternatives. In the original SMAA, a utility or value function models the DMs' preference structure, and the inaccuracy or uncertainty of the criteria is represented by probability distributions. In SMAA-3, ELECTRE III-type pseudo-criteria are used instead. Both methods compute for each alternative an acceptability index measuring the variety of different valuations that supports this alternative, and a central weight vector representing the typical valuations resulting in this decision. We seek answers to three questions: (1) how similar are the results provided by the decision models, (2) what kind of systematic differences exists between the models, and (3) how could one select indifference and preference thresholds of the pseudo-criteria model to match a utility model with given probability distributions?