Group Analytic Hierarchy Process Research Articles

Planning location of parcel lockers using group Analytic Hierarchy Process in Spherical Fuzzy environment

Parcel lockers have emerged as an effective solution to address inefficiencies in last-mile delivery. However, the selection of an appropriate location plays a crucial role in ensuring optimal service and enhanced logistic performance. To address this challenge, this work aims to define the best location for parcel lockers in the capital of Ireland, Dublin by conducting a novel decision-making model. The Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) has been adopted to deal with the uncertainty in the decision maker preferences, while the Euclidean Distance-Based Aggregation Method (EDBAM) has been conducted to aggregate the decision makers preferences. The proposed integrated model is an applicable approach to elude AHP deterministic disadvantages, moreover, it is the first application of SF-AHP and EDBAM to select parcel lockers’ location. The findings, including the identification of the top three optimal locations, namely “Post office,” “On commercial area,” and “High population density area,” along with their respective weight scores, provide valuable insights for policymakers making strategic decisions regarding parcel locker placements in Dublin city.

Resilient heuristic aggregation of judgments in the pairwise comparisons method

In decision-making methods, it is common to assume that the experts are honest and professional. However, this is not the case when one or more experts in the pairwise-based group decision-making framework, such as the group analytic hierarchy process, try to manipulate results in their favor. This paper aims to introduce two heuristics enabling detection of manipulators and minimizing their effect on the group consensus by diminishing their weights. The first heuristic is based on the assumption that manipulators will provide judgments that can be considered outliers with respect to those of the other experts in the group. The second heuristic assumes that dishonest judgments are less consistent than the average consistency of the group. Both approaches are illustrated with numerical examples and simulations.

A new method for evaluating the firing precision of multiple launch rocket system based on Bayesian theory

How to effectively evaluate the firing precision of weapon equipment at low cost is one of the core contents of improving the test level of weapon system. A new method to evaluate the firing precision of the MLRS considering the credibility of simulation system based on Bayesian theory is proposed in this paper. First of all, a comprehensive index system for the credibility of the simulation system of the firing precision of the MLRS is constructed combined with the group analytic hierarchy process. A modified method for determining the comprehensive weight of the index is established to improve the rationality of the index weight coefficients. The Bayesian posterior estimation formula of firing precision considering prior information is derived in the form of mixed prior distribution, and the rationality of prior information used in estimation model is discussed quantitatively. With the simulation tests, the different evaluation methods are compared to validate the effectiveness of the proposed method. Finally, the experimental results show that the effectiveness of estimation method for firing precision is improved by more than 25%.

Systematic Evaluation and Influencing Factors Analysis of Water Environmental Carrying Capacity in Taihu Basin, China

Systematic evaluation of water environment carrying capacity (WECC) is a prerequisite for achieving sustainable development, which reflects the water environment comprehensive condition of lake basin under the current economic development scenario. Therefore, taking the Taihu Basin as a case study, a scientific comprehensive evaluation index system of WECC was established based on the Pressure-State-Response (PSR) assessment framework, which included water resources (WR), pollution emission (PE), water quality (WQ), water ecology (WE), and land use (LU) sub-systems. An expert group was invited to determine the weights of each indicator using the group analytic hierarchy process (G-AHP) method, and the indicators in the WR, PE, WQ, WE, and LU sub-systems were 6.5%, 21.8%, 27.9%, 11.1%, and 32.9%, respectively. According to the evaluation results, the WECC index of Taihu Basin increased by 51.4% from 2007 to 2019, but it still slightly exceeded the carrying capacity of the water environment; the water quality and pollution discharge indices had the most significant improvement. Algal blooms are a major factor challenging WECC in the Taihu Basin. Therefore, the overall restoration of the water eco-system must receive more attention in the future.

Group AHP framework based on geometric standard deviation and interval group pairwise comparisons

The complexity of multi-criteria decision problems requires the involvement of a group of experts, who can contribute their knowledge, experience and opinions to the decision-making process. The aim of this study is to present a new group analytic hierarchy process (AHP) framework, called GSD-IJ. The main idea is to emphasize group satisfaction with the final decision, which is measured by the group satisfaction index. GSD-IJ is based on geometric mean and geometric standard deviation and allows aggregation of individual scalar valued judgments into interval group judgments. The width of the group interval judgments is controlled by the parameter λ, which ensures the acceptable degree of uncertainty of interval judgments, while providing the highest possible value of the group satisfaction index. Fuzzy preference programming is used to derive scalar-valued group weights from group interval pairwise comparison matrix. Three examples are given to evaluate and validate GSD-IJ. The results show that GSD-IJ performs well and is suitable for solving group multi-criteria decision problems.

A Comprehensive Utilization Efficiency Evaluation of Iron Tailings based on the Differential — Benefit Evaluation

At present, in the evaluation of iron tailings resources, the single evaluation of a certain aspect is limited to the qualitative evaluation, and there is no uniform standard in either theory or method. In this paper, based on the grey group analytic hierarchy process and fuzzy mathematics as the analysis tool, the benefit of the iron tailings resources is analyzed, From resource benefit, economic benefit, environmental benefit and social benefit several aspects to build the differential - efficiency index system and established the differential-benefit evaluation model and the influence of iron tailings resource evaluation of the weight of each index distribution, is obtained by correlation analysis and the likelihood of benefit index influencing the size of the order, to a certain extent, verified the rationality of the index weight, provides a theoretical guidance for iron tailings resource utilization.

Revenue Distribution Decision in Low-Carbon Supply Chain with Revenue Sharing Contract: An Analysis of the Third-Party Participation and GAHP

Apart from the three revenue sharing parameters, the other parameters of the revenue sharing contract (RSC) in a low-carbon supply chain cannot be precise values in most cases. As a result, adopting the RSC will cause challenges in the low-carbon supply chain. In this paper, to calculate the value of the revenue distribution parameter, a decision method based on multiple index is put forward. First, we construct an index system of revenue distribution based on the viewpoints of cost, efficiency, and satisfaction. Second, we propose the third-party participation (TPP) mechanism and the group analytic hierarchy process (GAHP) decision-making approach according to the premise that “heteronomy is better than self-discipline.” By the use of the case of company “A,” we demonstrated the applicability and practicability of the decision-making approach. The main contributions of this paper are twofold. First, we surveyed 22 experts and set up the 43 indexes, while also constructing the analytical hierarchy process matrix and explaining each index in depth. Second, the TPP mechanism and the GAHP method are used to calculate the value of each index and their sensitivity to the decision-making by the software of Yaahp12.0. Overall, this research can help the decision-makers of low-carbon supply chain in determining the ratio of revenue distribution and improving the applicability of revenue sharing contract.

An object–pressure–endurance–resilience system for assessing the vulnerability of coastal zone ecosystems

As a zone of interaction between land and sea, coastal zones are important carriers of the marine economy, and they are the focal point for strategies related to strengthening a country by means of the sea. As the coastal zones are where land and sea are most closely linked, they become a strategic area for achieving sustainable expansion of the blue economic space. Coastal zones have some capacity to cope with and recover from the adverse effects of ecological pressure, which is the coastal zone ecosystem vulnerability. However, given the vulnerability of coastal zone ecosystems and the existence of considerable ecological pressure, it is necessary to systematically assess coastal zones’ vulnerability and propose targeted countermeasures. First of all, this paper uses normative research methods and the methods that combine quantitative research with qualitative research to investigate the assessment of coastal zone ecosystem vulnerability and propose solutions for related governance. Second, based on an analysis of the shortcomings of existing methods, this study constructed an index system based on “object–pressure–endurance–resilience” (O-P-E-R) to assess coastal zone ecosystem vulnerability. O-P-E-R takes into account the triad of nature–society–culture and systematically defines ecosystem vulnerability. In the meantime, a combined weight calculation method that considers subjective and objective weights was proposed based on an improved group analytic hierarchy process (GAHP) method and the entropy weight method. Further, based on the standardization and normalization of indicator values, a method and scale for assessing coastal zone ecosystem vulnerability were proposed based on an improved matter-element model. In conclusion, the research has established a coastal zone ecosystem vulnerability assessment system that not only expand the safety management of coastal zone ecosystems but also provide a theoretical basis for governments to formulate related policies.

A Multi-Criteria Decision Support and Application to the Evaluation of the Fourth Wave of COVID-19 Pandemic.

The COVID-19 pandemic caused important health and societal damage across the world in 2020–2022. Its study represents a tremendous challenge for the scientific community. The correct evaluation and analysis of the situation can lead to the elaboration of the most efficient strategies and policies to control and mitigate its propagation. The paper proposes a Multi-Criteria Decision Support (MCDS) based on the combination of three methods: the Group Analytic Hierarchy Process (GAHP), which is a subjective group weighting method; Extended Entropy Weighting Method (EEWM), which is an objective weighting method; and the COmplex PRoportional ASsessment (COPRAS), which is a multi-criteria method. The COPRAS uses the combined weights calculated by the GAHP and EEWM. The sum normalization (SN) is considered for COPRAS and EEWM. An extended entropy is proposed in EEWM. The MCDS is implemented for the development of a complex COVID-19 indicator called COVIND, which includes several countries’ COVID-19 indicators, over a fourth COVID-19 wave, for a group of European countries. Based on these indicators, a ranking of the countries is obtained. An analysis of the obtained rankings is realized by the variation of two parameters: a parameter that describes the combination of weights obtained with EEWM and GAHP and the parameter of extended entropy function. A correlation analysis between the new indicator and the general country indicators is performed. The MCDS provides policy makers with a decision support able to synthesize the available information on the fourth wave of the COVID-19 pandemic.

Distance-based aggregation in group AHP

ABSTRACT The aggregation of evaluators’ preferences is a key problem in group decision making. We examine the recently proposed distance-based techniques and compare their efficiency to the traditional aggregation of individual preferences (AIP) methods in simulated Analytic Hierarchy Process (AHP) cases. We use the Kendall W statistic to measure the rank correlation among the individual priority vectors of the group and the common priority vector for the different aggregation approaches. Extensive simulations (altogether 88000 cases) show that both the Euclidean Distance-Based Aggregation Method (EDBAM) and the Aitchison Distance-Based Aggregation Method significantly outperform the traditional techniques in case of smaller and mid-sized priority vectors (at most six items to be compared). However, EDBAM outperform the AIP methods for all dimensions that is conventionally used in AHP, and its computation time is also low.

Can simple voting rules approximate the group AHP?

We analyze by means of simulations whether simple voting rules can approximate a group priority obtained by a standard aggregation method used in the group Analytic Hierarchy Process (AHP). Results show that under certain conditions, some voting rules provide relatively good approximations. It suggests a way of estimating the aggregated group priority easily in some situations. This short paper provides, by the nature of simulations, example results to consider the approximation issue, rather than general results.

A Group Multi-Criteria approach for development of a country COVID-19 indicator

The pandemic generated by the Sars Cov 2 corona virus is monitored, at the level of each country, every day, by several COVID-19 indicators. The present paper proposes a Group Multi-Criteria (GMC) approach for the development of a country COVID-19 indicator called COPACOV (COuntry Performance Against COVID-19) indicator. It is calculated starting from several country COVID-19 indicators measured separately, in a set a countries. COPACOV can identify which countries are more vulnerable to COVID-19 illnesses from several points of view taken together. The GMC approach is based on a hybrid method composed from the Group Analytic Hierarchy Process (GAHP) weighting method and from the Multicriteria Optimization and Compromise Solution (VIKOR) multi-criteria method. The aggregation (consensus) of the experts’ opinions, in the GAHP method is calculated with the geometric mean method. The VIKOR method uses the weights calculated by the GAHP method and calculates the COPACOV indicators. The proposed GMC approach is applied in a case study for a set of COVID-19 indicators and a set of Eastern European countries.

Assessment of sustainable urban development based on a hybrid decision-making approach: Group fuzzy BWM, AHP, and TOPSIS–GIS

The present study aimed to develop a practical framework consisting of GIS and MCDM to assess the development sustainability of Karaj, a city in the west of Tehran, Iran. Firstly, the influencing factors on sustainable urban development including seven criteria and 24 sub-criteria were screened and selected based on literature review, interviews with experts and Delphi technique. Then, the criteria were weighted and prioritized using Group Fuzzy BWM (GFBWM) and Analytic Hierarchy Process (AHP) methods. Fuzzy logic and Weighted Linear Combination (WLC) methods in GIS were used to determine the sustainability of Karaj for urban development. Finally, Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) was used to rank the identified areas. Our findings showed that the socioeconomic criterion and employment sub-criterion were the most important in AHP and GF-BWM methods. Both methods estimated that about 30% of the entire study area was highly sustainable in terms of urban development with no significant difference between the two methods. Finally, TOPSIS selected the center and north of the city as those with the highest priority. The integrated approach used in this study provided a flexible tool for analysis of the sustainable development, useful for planners and city managers.

A methodology for weighting indicators of value assessment of historic building using AHP with experts’ priorities

ABSTRACT The objective of this study is to provide a base for preservation of historic building, since weighting indicators is a foundation for value evaluation of historic building. A methodology of weighting indicators for the value assessment of historic building is proposed. The proposed methodology contains three methods. Method 1 assigns weights for indicators combining group analytical hierarchy process (AHP) with experts’ average priorities. Method 2 assigns weights for indicators combining group AHP with experts’ priorities by iterative clustering analysis. Method 3 assigns weights for indicators combining group AHP with experts’ priorities by sequential clustering analysis. A frame containing 5 categories and 18 indicators is constructed for value assessment of historic building in Hangzhou city of China. The proposed three methods are used to weight these indicators. The main conclusions are drawn as: 1) the proposed methodology is effective to weight indicators by expert group decision; 2) method 2 and method 3 are capable of selection of individual experts with extremal preference and assigning less priorities for them, which assist in reduction of impact of them on weighting indicators; 3) method 3 optimizes method 2 by elimination of the risk of non-convergence caused by unconvincing iterative termination; and 4) method 3 improves method 2 by reducing the heavy workload of iterative clustering.

Fuzzy Multi Criteria Group Decision for Determining the Relative Importance of Critical Success Factors in Accounting Information Systems

An effective Accounting Information System (AIS) will support the effectiveness of management functions in an enterprise. So, the aim of this research is to construct a prioritization-based taxonomy of critical success factors using fuzzy multi criteria group decision method: Fuzzy Group Analytical Hierarchy Process (FGAHP). In order to identify critical success factors of AIS, firstly, a deep literature survey was done. Then, a group of academic experts has been chosen from the accounting branch for pairwise comparison of critical success factors of AIS. After then, these chosen accounting experts evaluate the relative significance of critical success factors of the AIS which were defined from the literature. The results of the FGAHP analysis show that the most important success criteria of an AIS is the technological factors with weight 54%, and the external factors are the least important main success criteria for an AIS with weight 9%. Also, FGAHP evaluation of accounting experts decisions about sub criteria indicate that "security of knowledge” is the most important sub criteria with the weight 19%, “software supporting systems” with weight 14% is the second important one, and. “R&D activities and improvement” criteria with weight 8% is the third important sub criteria.

Symmetric projection group approach for promoting homogeneity in the analytic hierarchy process

The complexity of the socio-economic environment requires the involvement of a group of decision makers in the decision-making process. They can contribute the diversity of knowledge and experience that allow all the important aspects of the decision-making problem to be taken into account. In the aggregation process, the weights of the decision makers play an important role. In this paper we have focused on the group analytic hierarchy process (AHP). We emphasized the homogeneity of the opinions of the decision makers as the basis for determining the importance weights of the decision makers. We reviewed the projection method and its upgrades for determining decision makers weights and demonstrated with examples that they are not suitable for application in AHP. We proposed a new symmetric projection method that eliminates the imperfections of the previous projection methods. We proposed a Symmetric Projection Group Approach (SPGA) to derive group weights in AHP. To validate the SPGA, we selected four evaluation measures. The evaluation of the examples shows that the SPGA achieves good evaluation results compared to the other methods for deriving decision makers weights and is suitable for real-world applications.

Determining optimal group weights for consensus creation in AHP for three conflicting stakeholder groups by vector distance minimization

Involving three conflicting stakeholder groups in a decision making process and reaching their consensus is a common problem, especially in the case of public service development decisions, in which the public, the operator and the government participate as group decision makers. This paper presents a methodological novelty which is based on vector distance minimization and so is capable of creating an acceptable consensus among three evaluator groups with different interests and motivations, while it is also avoiding the pitfall of overgeneralization. The proof for the convexity of the problem and the solving algorithm are also demonstrated along with the calculation of the error of approximation. Moreover, we show a numerical example to prove that our proposed method is less sensitive to extremity compared to the most common mean-based aggregation techniques. Investigating the development of urban public transport systems, the paper presents three case studies using real preference data gained by an Analytic Hierarchy Process (AHP) survey involving three real conflicting stakeholder groups. Further, we conduct a comparison analysis based on concordance measure among the proposed consensus creation technique and other two well-proven consensus models: the zero-level GAHP and the Interval-AHP. The results indicate that the new method may be applied to several group AHP problems not only in transportation engineering but also in other fields of theoretical and real-world decision making.

Neutrosophic multi-criteria evaluation of sustainable alternatives for the structure of single-family homes

This paper proposes a methodology for the assessment of the sustainability among three different structural design alternatives for a single-family home. The response associated with each alternative has been measured using 43 indicators considering all stages of the life cycle. A decision-making model is carried out on the basis of a neutrosophic group analytical hierarchy process (NAHP-G) capturing the maximum information in terms of credibility, inconsistency and indetermination. The 9 criteria on which an expert group intervenes are finally evaluated using VIKOR. The results show that non-probabilistic uncertainties influence the weights obtained, with maximum deviations in the criteria between 11.91% and 4.95%, if compared to conventional AHP. From the methodology it is obtained that the technological alternative with non-conventional concrete performs best in sustainable terms. Although the industrialized option has less environmental impact, only the simultaneous consideration of the economic, environmental and social pillars in a project will lead to appropriate sustainable designs.

In defense of group fuzzy AHP: A comparison of group fuzzy AHP and group AHP with confidence intervals

Group aggregation of the Analytic Hierarchy Process (AHP), both with crisp and fuzzy numbers, is a widely researched field in group multiple criteria decision-making. Typically, if uncertainty needs to be reflected in the outcome of an AHP, triangular fuzzy numbers are used, although this is a controversial method, as many argue that the traditional 1–9 scale used in crisp AHP introduces uncertainty to the decision-making process, leaving no need for fuzzification. This research introduces the use of confidence intervals around the aggregated group mean to estimate the score ranges generated through group fuzzy AHP (GFAHP), as confidence intervals are simpler to calculate and more familiar to many. A comparison of the score ranges resulting from GFAHP and group aggregation using crisp numbers with confidence intervals around the group mean score, aggregating on individual priorities using both the arithmetic mean and geometric mean, was completed. The concept of using confidence intervals on crisp scores to generate score ranges was implemented through a case study to select a new all-wheel drive crossover vehicle. This study shows that confidence intervals introduce excessive uncertainty to the decision-making problem.

Data envelopment analysis for estimate efficiency and ranking operating rooms: a case study

Data Envelopment Analysis (DEA) is one of the non-parametric methods for evaluating each unit's efficiency. Limited resources in the healthcare system are the main reason for measuring the efficiency of hospitals. Because Operating Rooms (OR) are the most vital part of any hospital, we determine the factors affecting operating rooms' efficiency and evaluate the performance and ranking of operating rooms in 10 of Tehran's largest hospitals. This model's inputs include accuracy in scheduling surgeries, average turnover time, number of successful surgeries and live patients, number of canceled surgeries, number of surgical errors, and number of emergency surgery. Also, outputs consist of the number of operating rooms and equipment, the average number of beds, the number of employees, and the patient satisfaction rate. First, we determine the weight of inputs and outputs by Group Analytic Hierarchy Process (GAHP) with considering experts' ideas in 10 hospitals; then, we utilize three types of DEA model which are input-oriented CCR (CCR-I), output-oriented CCR (CCR-O), input-output oriented CCR (CCR_IO) and AP models to estimate the efficiency of ORs and rank them.