Ranking Of Decision Alternatives Research Articles

Ranking of Tourism Web Sites According to Service Performance Criteria with CRITIC and MAIRCA Methods: The Case of Turkey

Multi-Criteria Decision-Making (MCDM) methods enable the systematic ranking of decision alternatives by evaluating them with more than one maximized or minimized decision criterion. Multi-Criteria Decision-Making methods provide decision-makers with forms that include specified steps for calculating the importance weights of decision criteria and ranking decision alternatives. Weighting methods for calculating criterion weights are divided into subjective and objective. CRITIC method is one of the most widely used objective weighting methods in which criterion weights are determined according to the structure of the data. The MAIRCA method, a Multi-Criteria Decision Making method based on linear vector optimization, is widely preferred in the literature, especially in recent years, as it is also suitable for criteria with zero and negative values. This study aims to rank tourism websites, which play an essential role in terms of national tourism, according to nine service performance criteria. The CRITIC method determined the importance and weight values of the criteria, and the ranking of the websites was carried out by the MAIRCA method. The most decisive decision criterion in the website ranking was the live support and number of complaints. As a result of the ranking of the websites with the MAIRCA method, tripadvisor.com and seyahatyanımda.com took the first two places, while etstur.com and setur.com took the last two.

Implementasi Fuzzy Multi Criteria Decision Making Pada Seleksi Beasiswa Bank Indonesia

The Bank Indonesia Scholarship is a scholarship provided by Bank Indonesia for students at various universities, one of which is UIN Maulana Malik Ibrahim Malang. In the scholarship selection process, there are several criteria that affect the graduation of prospective scholarship recipients. However, often the process is not transparently. So a calculation method is needed, one of which is using Fuzzy Multi Criteria Decision Making (FMCDM). With FMCDM it can help to get an accurate and optimal decision on scholarship recipients. The FMCDM process begins with collecting information related to scholarships, scholarship applicants, and a set of criteria that will be used for consideration of scholarship acceptance. The set of criteria consists of 11 criteria, namely, Academic Achievement Index (GPA), international level achievement, national level achievement, provincial level achievement, district/city level achievement, father's occupation, mother's income, number of family dependents, house area, land and building tax, as well as electricity bills. The next step is to evaluate the fuzzy set by aggregating the weight of the criteria and the degree of compatibility of each alternative with the criteria. The aggregation result is called the fuzzy fit index which consists of 3 values, namely, the y value which represents the lower limit of the aggregation result, the q value which represents the middle limit, and the z value which represents the upper limit value. The three values are ranked using a ranking method for fuzzy numbers with a degree of optimism. So that the total integral value for each alternative will be obtained, which will be the decision in accepting the scholarship. From the results of the FMCDM, there is a ranking of decision alternatives from the highest priority to the lowest in determining scholarship acceptance.

An Analytic Hierarchy Process (AHP) Framework for Selecting Flexible Manufacturing System

The main objective of this paper is to propose a structured model for evaluating different Flexible Manufacturing System (FMS) using the Analytic Hierarchy Process (AHP). The paper aims to demonstrate how the model can help in taking correct decisions regarding the type of manufacturing flexibility needed for best FMS. This is because huge amount of money is invested to implement FMS in the industry. Hence, managers need to take judicious decision regarding the type and level of manufacturing flexibility. There are a number of manufacturing flexibility being reported in the literature. In this paper the most fundamental types i.e., machine, routing and product flexibility are examined. The AHP is aimed at integrating different measures into a single overall score for ranking decision alternatives. Its main characteristic is that it is base on pairwise comparison judgment. A usability evaluation of the AHP based model of FMS along with structure of the hierarchy is developed. The framework that is used in this example could serve as one of the tools for making a strategic decision. The effectiveness of our model is demonstrated through numerical examples.

STRATEGI PEMASARAN ROTI DI KING’S BAKERY DENGAN METODE ANALYTICAL HIERARCHY PROCESS (AHP)

ABSTRACT Every industry must make gradual improvements in order to be able to compete in the era of globalization. King's Bakery is a home industry that produces bread. The condition of bread marketing in the King's Bakery business has not been maximized. This study aims to determine the order of priority criteria and sub-criteria in the selection of a bread marketing strategy at King's Bakery and which strategy should be chosen by King's Bakery based on the Analytical Hierarchy Process (AHP) method. Analytical Hierarchy Process (AHP) is a method for ranking decision alternatives and selecting the best one with several criteria. The Analytical Hierarchy Process (AHP) develops a numerical value to find a ranking or priority order of various alternatives in solving a problem, based on the extent to which each alternative meets the decision maker's criteria. The results of this study obtained an assessment of the importance of the criteria in the selection of a bread marketing strategy showing the following priority or weighting scale: the first priority was place (0.546), the second and third priorities are products and distribution channels with the same value (0.231), and the fourth priority was the organization (0.104). From the results of the assessment of the level of alternative importance in the selection of bread marketing strategies, the priority scale or weights are as follows: the first priority was strategy A (3.614), the second priority was strategy C (2.366), the third priority was strategy B (2,000). The best bread marketing strategy that can be used as an alternative to improve bread marketing was strategy A, because it has the highest overall weight value. With technological innovation, it will accelerate production and facilitate marketing for the company.

Impact of Scenario Selection on Robustness

AbstractMultiple plausible future scenarios are being used increasingly in preference to a single deterministic or probabilistic prediction of the future in the long‐term planning of water resources systems. These scenarios enable the determination of the robustness of a system—the consideration of performance across a range of plausible futures—and allow an assessment of which possible future system configurations result in a greater level of robustness. There are many approaches to selecting scenarios, and previous studies have observed that the choice of scenarios might affect the estimated robustness of the system. However, these observations have been anecdotal and qualitative. This paper develops a systematic, quantitative methodology for exploring the influence of scenario selection on the robustness and the ranking of decision alternatives. The methodology is illustrated on the Lake Problem. The quantitative results obtained confirm the qualitative observations of previous works, showing that the selection of scenarios is important, as it has a large influence on the robustness value calculated for each decision alternative. However, we show that it has a relatively small influence on how those decision alternatives are ranked. This implies that despite the difference in robustness values, similar decision outcomes will be reached in this case study, regardless of the basis on which the scenarios are obtained. It is also revealed that the impact of the scenarios on the robustness values is due to complex interactions with the system model and robustness metrics.

A FBWM-PROMETHEE approach for industrial robot selection

In recent years, the selection of a robot for particular industrial purposes is one of the most challenging problems in the manufacturing environment based on automation and smartness for real-time decision-making. At present, several types of industrial robots with various capabilities, features, facilities, and specifications are available in the market. This makes the decision-making process more and more complicated due to the increase in complexity, advanced technologies, and features that are continually being incorporated into the robots by several manufacturers. The decision-maker needs to identify and select the best-suited robot to attain the desired output with precise application ability, and minimum cost. This paper tries to solve the robot selection problem using Fuzzy Best-Worst Method and PROMETHEE as the two most appropriate multi-criteria decision-making (MCDM) methods for weighting criteria and ranking of decision alternatives, respectively.

Estimating criteria weight distributions in multiple criteria decision making: a Bayesian approach

A common way to model decision maker (DM) preferences in multiple criteria decision making problems is through the use of utility functions. The elicitation of the parameters of these functions is a major task that directly affects the validity and practical value of the decision making process. This paper proposes a novel Bayesian method that estimates the weights of criteria in linear additive utility functions by asking the DM to rank or select the best alternative in groups of decision alternatives. Our method computes the entire probability distribution of weights and utility predictions based on the DM’s answers. Therefore, it enables the DM to estimate the expected value of weights and predictions, and the uncertainty regarding these values. Additionally, the proposed method can estimate the weights by asking the DM to evaluate few groups of decision alternatives since it can incorporate various types of inputs from the DM in the form of rankings, constraints and prior distributions. Our method successfully estimates criteria weights in two case studies about financial investment and university ranking decisions. Increasing the variety of inputs, such as using both ranking of decision alternatives and constraints on the importance of criteria, enables our method to compute more accurate estimations with fewer inputs from the DM.

Robustness Metrics: How Are They Calculated, When Should They Be Used and Why Do They Give Different Results?

AbstractRobustness is being used increasingly for decision analysis in relation to deep uncertainty and many metrics have been proposed for its quantification. Recent studies have shown that the application of different robustness metrics can result in different rankings of decision alternatives, but there has been little discussion of what potential causes for this might be. To shed some light on this issue, we present a unifying framework for the calculation of robustness metrics, which assists with understanding how robustness metrics work, when they should be used, and why they sometimes disagree. The framework categorizes the suitability of metrics to a decision‐maker based on (1) the decision‐context (i.e., the suitability of using absolute performance or regret), (2) the decision‐maker's preferred level of risk aversion, and (3) the decision‐maker's preference toward maximizing performance, minimizing variance, or some higher‐order moment. This article also introduces a conceptual framework describing when relative robustness values of decision alternatives obtained using different metrics are likely to agree and disagree. This is used as a measure of how “stable” the ranking of decision alternatives is when determined using different robustness metrics. The framework is tested on three case studies, including water supply augmentation in Adelaide, Australia, the operation of a multipurpose regulated lake in Italy, and flood protection for a hypothetical river based on a reach of the river Rhine in the Netherlands. The proposed conceptual framework is confirmed by the case study results, providing insight into the reasons for disagreements between rankings obtained using different robustness metrics.

An AHP-Evaluation Models for Ranking Construction Tenders Using Simulation: A Case Study in Kurdistan Region of Iraq

In ranking decision alternatives, Analytic Hierarchy Process is regarded as one of themost successful techniques to deal with multiple criteria decision making problems.Recognizing that tender evaluation is a typical multi-criteria decision making problem,this paper introduces an evaluation approach based on AHP methodology for rankingvarious alternative options, each represents a construction project the tender, and thenselecting the best one. The proposed model can guide decision makers in constructionindustry identify contractors with the best potential to deliver satisfactory outcomes in afinal process of tender selection in Kurdistan Region of Iraq. Moreover, in order toreduce the inherent uncertainty within the AHP, which may significantly affect thedecision process, a new methodology is proposed by using simulation. This model istested by a hypothetical scenario where six tenders are evaluated and then, the bestcandidate is selected. Furthermore, the criteria used for the tender selection in the modeland the significance of each criterion had been arrived at by conducting the first surveystudy for public and private organizations in Kurdistan Region of Iraq.

Applying AHP to Evaluate Hydropower Projects of Lao PDR in Implementation of the Environmental Management and Monitoring Plan

Environmental protection is a major issue that is critical to the sustainable development of the country. The government of Lao PDR is taking the energy plan into consideration in order to manage and mitigate the negative impacts and to monitor the mitigation programs. Usually, the Environmental Management and Monitoring Plan (EMMP) of the Environmental Impact Assessment (EIA) report contains the terms and conditions with which the project developers must comply. In order to ensure that a project developer fully implements its commitment under EMMP, the MoNRE of Lao PDR have developed an environmental monitoring guideline and checklist which contains key indicators and parameters to be used by the monitoring authorities. The objective of this study is to evaluate the implementation of EMMP performed by 5 hydropower projects existing in Lao PDR, namely, Nam Thurn2, Nam Thurn Hinboun, Nam Ngum2, Num Lik1-2 and Num Ngum5. This study analyzed the monitoring data under multiple parameters including water quality, fish and fisheries, waste and pollution, watershed, downstream river flow, camp sites and construction sites, and reports, undertaken by different inspectors. The Analytic Hierarch Process (AHP) is accepted to be a powerful and flexible method for ranking decision alternatives and selecting the best ones when the decision makers have multiple criteria. Therefore, it is a selected tool used for determining the optimal hydropower project in Lao PDR based on the collected monitoring data. A case study was conducted to understand which one could be considered as the environmental friendly project and which parameter has the importance role to the accomplishment of project development.

Exploring the future: Runtime scenario selection for complex and time-bound decisions

Scenarios are designed to support decision-makers in gaining a better understanding of the consequences of decisions. Despite their popularity in IT for Foresight, a major obstacle is the complexity of strategic decisions and the resulting multitude of scenarios. Therefore choices need to be made, which scenarios to fully work out, by which experts and in which level of detail. This paper presents an approach to support making these trade-offs between accuracy and resources spent by prioritising scenarios based on their significance for the decision even on the basis of incomplete information. This approach combines theoretical findings in decision theory with results that were elicited in interviews and workshops with decision-makers and experts. In this manner, we ensure to adhere to time and effort constraints of the involved experts, while taking into account the decision-makers' preferences and requirements. The emergency management use-case shows that the resulting reduced set of scenarios leads to the same ranking of decision alternatives as the entire set of scenarios.

Robust optimization analysis for multiple attribute decision making problems with imprecise information

This paper considers ranking decision alternatives under multiple attributes with imprecise information on both attribute weights and alternative ratings. It is demonstrated that regret results from the decision maker’s inadequate knowledge about the true scenario to occur. Potential optimality analysis is a traditional method to evaluate alternatives with imprecise information. The essence of this approach is to identify any alternative that outperforms the others in its best-case scenario. Our analysis shows that potential optimality analysis is optimistic in nature and may lead to a significant loss if an unfavorable scenario occurs. We suggest a robust optimization analysis approach that ranks alternatives in terms of their worst-case absolute or relative regret. A robust optimal alternative performs reasonably well in all scenarios and is shown to be desirable for a risk-concerned decision maker. Linear programming models are developed to check robust optimality.

RANKING DECISION ALTERNATIVES BY INTEGRATED DEA, AHP AND GOWER PLOT TECHNIQUES

Data Envelop Analysis (DEA) and Analytic Hierarchy Process (AHP) are widely used methods in ranking decision alternatives. However, current DEA models are difficult to discriminate decision-making units through articulating the decision makers' preferences. While AHP and Gower plot models have to specify complete pairwise preferences without providing assisting information. This study develops an iterative method of ranking decision alternatives by integrating DEA, AHP and Gower plot techniques. The developed method first utilizes a modified DEA model to narrow the ranges of a decision maker's preferences. Then, the tentative ranks of the decision alternatives, computed by embedding the decision maker's preferences, are depicted via Gower plots to illustrate the cardinal and ordinal inconsistencies of these preferences. The decision maker then adjusts the preferences iteratively until the inconsistencies are within the tolerance.

Data transformation in the evidential reasoning‐based decision making process

AbstractThis paper describes the application of an evidential reasoning (ER)‐based decision making process to multiple‐criteria decision making (MCDM) problems having both quantitative and qualitative criteria. The ER approach is based on the decision theory and the theory of evidence and it uses the concept of ‘degree of belief’ to assess decision alternatives on each attribute. When faced with MCDM problems, evaluation and selection or ranking of alternatives appear to be both challenging and vital to arrive at a rational and robust decision. In the presence of both qualitative and quantitative evaluations in an MCDM problem, it is necessary, when using the ER‐based decision making process, to transform or convert quantitative data into a belief structure using a number of grades so that the converted belief structure and the original quantitative data are equivalent in values or utilities. This paper suggests three scenarios for data transformation and examines how the ranking of decision alternatives is changed when different scenarios of data transformation are used. Ranking of UK universities using the ER approach is illustrated as an example.

An Application of the Analytic Network Process to the Advertising Media Budget Allocation Decision

This study developed and tested a comprehensive model for media selection and budget allocation using the analytic network process (ANP; Saaty, 1996). ANP can be used to solve complex decision-making problems by integrating different measures (both qualitative/intangible and quantitative/tangible) into a single overall score for ranking decision alternatives. The resultant model may be used by expert or novice media planners with equal effectiveness. This study demonstrated how this model may be used to allocate media dollars for 2 industries: airlines and financial services.

Development of a media selection model using the analytic network process

The authors develop and test a comprehensive model for media selection utilising the Analytic Network Process (ANP). ANP is a flexible and powerful multi-attribute decision aid developed by Saaty (1996) for solving complex decision-making problems. It is aimed at integrating different measures (both qualitative/intangible and quantitative/tangible) into a single overall score for ranking decision alternatives. In applying the ANP method, the authors specifically incorporate web/internet media advertising into their list of media alternatives, using many of the same standard media attributes that have typically been employed in comparing more traditional media. The result is a model that may be utilised by expert and/or novice media planners with equal effectiveness.

Eliciting and mapping qualitative preferences to numeric rankings in group decision making

Group work is becoming the norm in organizations. From strategy planning committees to quality management teams, organizational members are collaborating on problem solving. One area of team support that is often desired is the scoring and ranking of decision alternatives on qualitative/subjective domains, and the aggregation of individual preferences into group preferences. In this paper we present a new conceptual approach to qualitative preference elicitation and aggregation. This approach is based on well established decision analysis techniques. It significantly advances the state of the art of group decision making by addressing four common limitations: (1) the inability to deal with vagueness of human decision makers in articulating preferences; (2) difficulties in mapping qualitative evaluation to numeric estimates; (3) problems in aggregating individual preferences into meaningful group preference; and (4) the lack of simple user friendly techniques for dealing with a large number of decision alternatives. Our approach is easy to implement in stand alone personal computers and groupware. We illustrate this with a real-world problem.

A multi-attribute preference model for evaluating the reforestation chain alternatives of a forest stand

This paper presents a method, based on multi-attribute utility theory, for choosing the reforestation chain in a forest stand. The method is developed mainly for analysing and supporting the decision-making of non-industrial forest landowners. By using the decision analysis model, all kinds of objectives, qualitative as well as quantitative, can be analytically dealt with, and alternative reforestation chains can be evaluated with regard both to overall utility and to each specific objective. The decision alternative which maximises overall utility is recommended as most suitable. Values of reforestation chain alternatives with regard to an objective which cannot be measured reliably enough using quantitative production functions are determined via preference functions describing the importance of making sub-choices of chains and the desirabilities of sub-choice alternatives, with regard to the objective in question. Parameters of preference functions are estimated on the grounds of pairwise comparisons between decision elements, using the eigenvalue method as presented by T.L. Saaty. Timber production values are estimated on the basis of the discounted value of net revenues. Based on the interpretation of the parameters of the preference model as marginal rates of substitution, wide-ranging sensitivity analyses can be carried out, e.g. on the effects of changing the weighting of objectives on the ranking of decision alternatives.