The state of the art development of AHP (1979-2017): A literature review with a social network analysis

Although many papers describe the evolution of the analytic hierarchy process (AHP), most adopt a subjective approach. This paper examines the pattern of development of the AHP research field using social network analysis and scientometrics, and identifies its intellectual structure. The objectives are: (i) to trace the pattern of development of AHP research; (ii) to identify the patterns of collaboration among authors; (iii) to identify the most important papers underpinning the development of AHP; and (iv) to discover recent areas of interest. We analyse two types of networks: social networks, that is, co-authorship networks, and cognitive mapping or the network of disciplines affected by AHP. Our analyses are based on 8441 papers published between 1979 and 2017, retrieved from the ISI Web of Science database. To provide a longitudinal perspective on the pattern of evolution of AHP, we analyse these two types of networks during the three periods 1979?1990, 1991?2001 and 2002?2017. We provide some basic statistics on AHP journals and researchers, review the main topics and applications of integrated AHPs and provide direction for future research by highlighting some open questions

The state of the art development of AHP (1979-2017): a literature review with a social network analysis

Although many papers describe the evolution of the analytic hierarchy process (AHP), most adopt a subjective approach. This paper examines the pattern of development of the AHP research field using social network analysis and scientometrics, and identifies its intellectual structure. The objectives are: (i) to trace the pattern of development of AHP research; (ii) to identify the patterns of collaboration among authors; (iii) to identify the most important papers underpinning the development of AHP; and (iv) to discover recent areas of interest. We analyse two types of networks: social networks, that is, co-authorship networks, and cognitive mapping or the network of disciplines affected by AHP. Our analyses are based on 8441 papers published between 1979 and 2017, retrieved from the ISI Web of Science database. To provide a longitudinal perspective on the pattern of evolution of AHP, we analyse these two types of networks during the three periods 1979–1990, 1991–2001 and 2002–2017. We provide some basic statistics on AHP journals and researchers, review the main topics and applications of integrated AHPs and provide direction for future research by highlighting some open questions

Extended Topics in the Integration of Data Envelopment Analysis and the Analytic Hierarchy Process in Decision Making.

The Analytic Hierarchy Process (AHP) is a procedure, which can only consider relative priorities as estimated by decision-makers. A Data Envelopment Analysis (DEA) model is a data-oriented approach for evaluating the relative efficiency of a group of entities referred to as Decision Making Units (DMUs). This research work integrates and combines positive aspects of AHP\u27s estimated qualitative data and DEA\u27s quantitative data. This combination is accomplished by specifying two variants of the DEA methodology for selection of the best DMU. Initially the priority weights of AHP are integrated with the DEA methodology to provide results that are logic based. Next, a method is developed to work backwards through the DEA model to provide values that would be the required results from an AHP formulation to give the same result in DEA. The objective of the research is to propose variants of DEA that would possibly improve the results and also integrate subjective data. Through the application of the methods developed in this research, it is believed that the acceptability of the results obtained from DEA analysis can be improved

An Optimization-based approach for vaccine prioritization

An effective vaccine prioritization process is essential to prevent the many issues that currently weaken global vaccination efforts. Identifying challenges associated with vaccine development is important when considering which initiatives will provide immunization that is effective, affordable, and easy to administer. The process of establishing priorities for vaccine development is complicated, though, by the conflicting interests of multiple stakeholders involved in the vaccine market. Additionally, uncertainties exist regarding: (1) the resources and time required for vaccine development, (2) the expected benefits of development, and (3) the anticipated demand for vaccination, further complicating the prioritization process. This study proposes a decision-support tool for prioritizing vaccine initiatives through the use of mathematical optimization models. The tool allows a panel of decision makers to assess vaccine candidates over multiple criteria with information that is both quantitative and qualitative. This assessment is the result of a methodology that integrates Data Envelopment Analysis and the Analytic Hierarchy Process. The decision-support tool could be used by researchers and funding agencies to determine which vaccine initiatives should be: more effective, affordable, profitable, reliable, easier to use and store, and more suitable to the needs of multiple populations from diverse locations and having multiple logistic needs

VIKOR multi-criteria decision making with AHP reliable weighting for article acceptance recommendation

DSS is built to support the solution recommendation of a problem. AHP and VIKOR are examples of DSS method. Due to VIKOR’s subjective weighting, this study combines the AHP and VIKOR approach to create a better and more reliable decision support system. The DSS is used to recommend article acceptance using five criteria: originality, quality, clarity, significance, and relevance. The results showed that AHP-VIKOR outperforms the performance of VIKOR. AHP weighting reliably replaces the subjective VIKOR’s initial weighting. The AHP-VIKOR result is more accurate and steadier than VIKOR. Thus, AHP-VIKOR can be presented as a proposed approach for creating a recommendation of scientific article acceptance

The Data Envelopment Analytic Hierarchy Process (DEAHP) Approach in the Evaluation of Commercial Credit Applications

In this study, four companies operating in the same sector that had applied for commercial credit from one of the largest private capital banks of Turkey were compared in terms of their performance and the company with the credit application most likely to be satisfied was determined. The Data Envelopment Analytic Hierarchy Process, created by the joint (hybrid) use of the Data Envelopment Analysis and Analytic Hierarchy Process was used in this study. Overall weights were obtained by summing the local weights obtained by Data Envelopment Analysis. Criteria, sub-criteria and weights regarding the alternatives in the hierarchy were calculated according to the Analytic Hierarchy Process and The Data Envelopment Analytic Hierarchy Process methods and the results were similar. According to the findings obtained with both approaches, company ethics and intelligence were determined to be the most important criteria, whereas the company’s sales and marketing structure and sectoral structure were determined to be the least important criteria. On the other hand, according to both the Analytic Hierarchy Process and Data Envelopment Analytic Hierarchy Process approaches, Company 2 was determined to be the most appropriate company whose credit application would be satisfied. Keywords: Commercial credit application; Credit application evaluation model; Multi Criteria Decision Making; Data Envelopment Analytic Hierarchy Process

Assessment of Irrigation Water Use Efficiency in Citrus Orchards Using AHP

[EN] Irrigation water use efficiency, the small size of the orchards, and part-time farmers are major issues for Spanish citriculture. How should irrigation water use efficiency be assessed? Does irrigation water use efficiency improve when increasing the size of the orchards? Are full-time farmers more efficient in irrigation water use than part-time ones? To address these three questions, we propose to apply a new multicriteria approach based on the analytic hierarchy process (AHP) technique and the participation of a group of experts. A new synthetic irrigation efficiency index (IEI) was proposed and tested using data from an irrigation community (IC) and a cooperative of farmers in the East of Spain. The results showed that the size of the orchards had no relation with the IEI scoring but full-time farmers tended to have better IEI scores and, thus, were more efficient. These results were obtained from a sample of 24 orchards of oranges, navelina variety, growing in a very similar environment, and agronomical characteristics. The proposed methodology can be a useful benchmarking tool for improving the irrigation water management in other ICs taking into account the issues related to farm data sharing recorded during the case study.The APC was funded by the Project 2019ES06RDEI7346 Improving the use of water and energy in modernized irrigation of fruit trees (GO InnoWater), funded by the Spanish Rural Development Program (2014-2020): EAFRD and MAPA.Poveda Bautista, R.; Roig-Merino, B.; Puerto, H.; Buitrago Vera, JM. (2021). Assessment of Irrigation Water Use Efficiency in Citrus Orchards Using AHP. International Journal of Environmental research and Public Health (Online). 18(11):1-14. https://doi.org/10.3390/ijerph18115667S114181

An Integration of Rank Order Centroid, Modified Analytical Hierarchy Process and 0-1 Integer Programming in Solving A Facility Location Problem

Hadhramout province is the major producer of dates in The Republic of Yemen. Despite producing substantial quantity and quality of dates, the business losses are still high. The situation worsens with the widespread of the black market activities. Recently, the Yemeni government has issued an agreement stating the importance of building a date palm packaging factory as a resolution to the problems. Hence, this study aims to identify the best location for a date palm packaging factory among the seven districts which produce most of the date palm supplies in Hadhramout. The selection was based on eleven criteria identified by several representatives from the farmers and the local councils. These criteria were market growth, proximity to the markets, proximity to the raw materials, labor, labor climate, suppliers, community, transportation cost, environmental factors, production cost, and factory set up cost. The level of importance and the respective weight of each criterion were calculated using two different approaches, namely, Analytic Hierarchy Process (AHP) and Rank Order Centroid (ROC). In applying AHP, a slight modification was made in the pairwise comparison exercises that eliminated the inconsistency problem faced by the standard AHP pairwise comparison procedure. Likewise, in applying ROC, a normalization technique was proposed to tackle the problem of assigning weights to criteria having the same priority level, which was neither clarified nor available in the standard ROC. Both proposed techniques revealed that suppliers were the most important criterion, while community was regarded to be the least important criterion in deciding the final location for the date palm factory. Combining the criteria weights together with several hard and soft constraints that were required to be satisfied by the location, the final location was determined using three different mathematical models, namely, the ROC combined with 0-1 integer programming model, the AHP combined with 0-1 integer programming model, and the mean of ROC and AHP combined with 0-1 integer programming model. The three models produced the same result; Doean was the best location. The result of this study, if implemented, would hopefully help the Yemeni government in their effort to improve the production as well as the management of the date palm tree in Hadhramout

Multi-Dimensional Assessment of Transit System Efficiency and Incentive-based Subsidy Allocation

Over the past several decades, contending with traffic congestion and air pollution has emerged as one of the imperative issues across the world. Development of a transit-oriented urban transport system has been realized by an increasing number of countries and administrations as one of the most effective strategies for mitigating congestion and pollution problems. Despite the rapid development of public transportation system, doubts regarding the efficiency of the system and financing sustainability have arisen. Significant amount of public resources have been invested into public transport; however complaints about low service quality and unreliable transit system performance have increasingly arisen from all walks of life. Evaluating transit operational efficiency from various levels and designing incentive-based mechanisms to allocate limited subsidies/resources have become one of the most imperative challenges faced by responsible authorities to sustain the public transport system development and improve its performance and levels of service. After a comprehensive review of existing literature, this dissertation aims to develop a multi-dimensional framework composed of a series of robust multi-criteria evaluation models to assess the operational and financial performance of transit systems at various levels of application (i.e. region/city level, operator level, and route level). It further contributes to bridging the gap between transit efficiency evaluation and the subsequent subsidy allocation by developing a set of incentive-based resource allocation models taking various levels of operational and financial efficiencies into consideration. Case studies using real-world transit data will be performed to validate the performance and applicability of the proposed models