Application Of Analytic Hierarchy Process Research Articles

Improvement of competitiveness through the application of analytic hierarchy process, game theory, decision trees and design of experiments tools

Competitiveness is important for all companies. Because qualitative and quantitative factors are associated with it, strategic decisions must be supported by different analytical tools. In this work, we describe the application of specific tools to improve the expansion strategy for a food supplements company which is facing strong competitors. Two main alternatives were considered: increasing the production of the current products, and extending the company’s portfolio by adding new products. In contrast to other works, the competitors’ key features and likely response were considered as determinant factors for the assessment of these alternatives. These were addressed through analytic hierarchy process and game theory tools. Then, economic assessment and optimization of the new products’ features were addressed through decision tree and design of experiments tools. The results of this approach corroborate its suitability for other companies where appropriate strategic actions must be formulated in advance of the possible competitors’ response to increase competitiveness.

Methodology to Optimize Quality Costs in Manufacturing Based on Multi-Criteria Analysis and Lean Strategies

Manufacturing quality cost optimization is a priority in any manufacturing sector due to quality issues impacting companies’ reputations and has financial consequences. Quality costs are composed of tangible and intangible costs, however, only tangible costs used to be analyzed because there is no suitable methodology for measuring intangible costs. In this context, an innovative decision support system is developed with an empirical base, applying Analytical Hierarchy Process (AHP), Analytical Network Process (ANP), and Lean methodology to reduce all quality costs in an efficient way. In quality departments, perceptions, thoughts, and judgments (intangible costs) are not measured and controlled. This study develops an innovative methodology that allows to address this issue in an effective way. Another major innovation is the application of both multi-criteria methodologies to obtain the best combined result for decision making and the optimization of this result, developing an effort–impact matrix based on Lean manufacturing methodology. This system speeds up the decision-making process and assures its efficiency for quality department applications. Moreover, this decision support system may be applicable to any manufacturing sector.

Quantifying villager readiness in rural tourism: an application of analytical hierarchy process (AHP)

ABSTRACT While many studies neglect to assess villager readiness for tourism-based village development, this present study addresses this issue by providing a quantitative measurement to evaluate villager readiness towards tourism programmes. Using Balesari village -an emerging tourism village in Indonesia- as a case, the level of readiness was measured. To better capture the actual condition, the present study applied Analytical Hierarchy Process (AHP) to weigh each dimension based on stakeholders’ priority. Drawing from the key stakeholders’ dimension weighting and field survey of 187 respondents, we can quantify the readiness level and provide detailed descriptions of villager readiness in a tourism development project. The result of this study may inform policymakers in assessing rural tourism development projects from the villagers’ perspective.

Groundwater potential mapping using multi-criteria decision, bivariate statistic and machine learning algorithms: evidence from Chota Nagpur Plateau, India

Increased consumption of water resource due to rapid growth of population has certainly reduced the groundwater storage beneath the earth which leads certain challenges to human being in recent time. For optimal management of this vital resource, exploration of groundwater potential zone (GWPZ) has become essential. We have applied Analytical Hierarchy Process (AHP), Frequency Ratio (FR) and two machine learning techniques specifically Random Forest (RF) and Naïve Bayes (NB) here to delineate GWPZ in Gandheswari River Basin in Chota Nagpur Plateau, India. To achieve the goal of the study, twelve factors that determine occurrence of groundwater have been selected for inter-thematic correlations and overlaid with location of wells. These factors include elevation, drainage density, slope, lithology, geomorphology, topographical wetness index (TWI), distance from the river, rainfall, lineament density, Normalized Difference Vegetation Index (NDVI), soil, and Land use and Land cover (LULC). A total 170 points including 85 in well site and 85 in non-well site have been selected randomly and allocated into two parts: training and testing at the share of 70:30. The implemented methods have significantly provided five GWPZs specifically Very Good (VG), Good (G), Moderate (M), Poor (P) and Very Poor (VP) with high and acceptable accuracy. The study also finds that geomorphology, slope, rainfall and elevation have greater importance in shaping GWPZs than LULC, NDVI, etc. Model performance has been tested with receiver operator characteristics (ROC), Accuracy (ACC), Kappa Coefficient, MAE, RMSE, etc., methods. Area under curve (AUC) in ROC curve has revealed that accuracy level of AHP, FR, RF and NB is 78.8%, 81%, 85.3% and 85.5, respectively. The machine learning techniques coupled with AHP and FR unveil effective delineation of groundwater potential area in said river basin which by genetically offers low primary porosity due to lithological constrains. Therefore, the study can be helpful in watershed management and identifying appropriate location wells in future.

Application of Analytic Hierarchy Process and weighted sum techniques for green tourism potential mapping in the Gangetic West Bengal, India

Application of Analytic Hierarchy Process and weighted sum techniques for green tourism potential mapping in the Gangetic West Bengal, India

Application of Analytical Hierarchy Process (AHP) for Assessment of Collection and Transportation of Solid Waste: An Empirical Study

Cities and Urban Local Bodies (CULB) are considered to be the engines of economic growth and any significant improvement in their operational efficiency will lead to a positive impact on the economy. The major portion of expenditure on Solid waste management (SWM) of CULBs is spent on waste collection and transportation activities. To enhance the efficiency of SWM, it is essential to collect and transport solid waste in a scientific manner. As a result, systematic solid waste collection and transportation will effectively resolve and improve SWM concerns. In this paper, Analytical Hierarchy Process (AHP) method is adopted to appraise various alternatives of solid waste collection and transportation methods of municipal solid waste in Visakhapatnam city, India. The additive normalization method is applied for calculating the criteria weights. The fairness of judgment is checked by the consistency ratio. To calculate AHP accurately and fast, a decision support system was built. The findings of the study will be beneficial in evaluating existing solid waste collection and transportation processes to improve the operational efficiency of managing SWM.

Prioritizing intervention measures to prevent inappropriate self-medication practices using the Analytical Hierarchy Process

BackgroundUnited Nations Sustainable Development Goal 3 outlines the target of reducing premature mortality from non-communicable diseases by one third through prevention and treatment by 2030. In low and middle-income countries (LMICs) like Nepal, a significant number of people do not have accessible and affordable healthcare services available to them, leading to self-medication practices (SMP). Limited numbers of health professionals, ineffective regulation and easy availability of prescription medicines encourage the use of inappropriate SMP, which could result in health risks. ObjectivesThe objection of the study is to test the application of Analytical Hierarchy Process (AHP) for prioritizing the intervention measures for preventing inappropriate SMP. MethodsThe 25 experts were included in the study, out of which only 16 experts passed the consistency test. Data were collected using a structured questionnaire by the application of AHP model for ranking the intervention measures for preventing inappropriate SMP from March 2020 to May 2020. During this process, the purposively selected experts compared seven intervention measures based on three criteria: control use of prescription and non-prescription medicine, knowledge regarding the medicine and its use, and minimizing healthcare cost. ResultThe criteria, “control use of prescription and non-prescription medicine” was judged 3.58 times and 1.53 times more important than to “minimize the healthcare cost” and “knowledge regarding the medicine and its use” respectively. “Regulation of prescription and non-prescription dispensing practice” was the most prioritized intervention measure to prevent inappropriate SMP with a priority score of 20.68% followed by the “accessibility of healthcare system” (19.27%) and “awareness program for the consumers” (17.13%). ConclusionThe AHP method can be used in decision-making related to prioritizing the intervention measures to prevent inappropriate SMP. Among the seven intervention measures considered, “regulation of prescription and non-prescription dispensing practice” was the most preferred intervention measure to improve SMP followed by “access to healthcare” and an “awareness program”.

Hierarchical Representation of Decision-Making in Chartering a Vessel on a Voyage Charter

This paper presents a decision-making method (analytic hierarchy process) for choosing a charter option by means of a subjective preference vector. Analytic hierarchy process (AHP) is a rather general methodology for solving a broad range of weakly structured decision-making problems that combines a fairly simple mathematical method with the manager’s knowledge, experience, and imagination. This paper investigates AHP application by a manager who is not an expert in chartering. To describe the method, the paper presents a case study of chartering a vessel to freight bulky, heavy cargo.

Progressing the aerospace performance factor toward nonlinear interactions.

Evaluation of safety performance remains central to any safety and risk management. Currently, there are very few support tools and methods which allow for quantitative approach in this domain. One of the successful methods available to this end is the Aerospace Performance Factor (APF). The method is based on hierarchical clustering of taxonomy-based safety performance indicators, using simple and intelligible formula to compute the overall safety performance signal. The work presented in this study deals with one of the APF shortcomings, namely the absence of nonlinear relations among the performance indicators to capture more accurately the risk in the assessed system. It proposes an addition of new decision criteria behind the APF method as part of the application of Analytical Hierarchy Process (AHP), namely the impact of respective performance indicator on other indicators, regardless of their hierarchical structure. This addition leads to relative changes of performance indicators significance, where those with the highest potential for nonlinear interactions among the entire set of performance indicators are emphasized and the change in their weight ultimately leads to changes in the overall APF signal. The study results indicate that the extended APF signal is refined in terms of extremes and it draws more accurate picture about the actual safety performance, eventually supporting better identification of deviations from its acceptable values. The study was experimentally carried out in the aviation with data from the European Central Repository (ECR) originating from United Kingdom during the years 2013-2015 and verified further on data sets from Finland and Denmark.

Improved Routing Protocol Based on Multiobjective Optimization in Industrial Robot Networks

This paper decomposes the routing process of industrial robot network using the application of analytic hierarchy process in decision-making. The influence of four factors, such as path length, data integrity, energy consumption, and receiving delay, on routing effect is analyzed. Simultaneous interpreting routes are selected to achieve the purpose of routing. Simulation results show that this method can more comprehensively consider the factors affecting routing and is superior to the existing methods in terms of energy consumption, data integrity, and transmission delay.

Application of AHP and PESTEL-SWOT Analysis on The Study of Military Amphibious Aircraft Acquisition Decision Making in Indonesia

Indonesia’s characteristics as an archipelagic state along with the increase of traditional and non-traditional threats in Indonesia require the ownership of military amphibious aircraft to oversee its maritime territories and perform logistics distribution to remote areas with minimum accessibility, especially its outermost islands. This study applied a combination of analytic hierarchy process (AHP), Political, Economic, Social, Techonology, Environment, and Legal (PESTEL) and Strength, Weakness, Opportunity, and Threat (SWOT) analysis to conduct a structured, systematic, measurable, and comprehensive decision-making process for selecting military amphibious aircraft and prescribe strategic recommendations on the acquisition plan. By using 3 criteria, 14 sub-criteria, and 3 alternative aircraft models, the results of AHP analysis showed that the Beriev Be-200 aircraft are the most preferred aircraft by the Indonesian users. The results of PESTEL-SWOT analysis show that good diplomatic relations between Indonesia and the manufacturer’s country of origin, users’ support to the plan, and user’s ability to adapt in operating and maintaining the aircraft support this decision. Meanwhile, limited fiscal capacity and domestic aircraft maintenance facilities/depots, as well as the risk of spare parts scarcity, have to be addressed for Indonesia to acquire its own military amphibious aircrafts.

Selection of Khadi fabrics for optimal comfort properties using multi-criteria decision-making technique

PurposeKhadi fabrics are known for their unique comfort properties which are attributed to their unique structural and functional properties. For getting optimal comfort from a collection of available Khadi fabrics, further exploration is needed. Ranking the Khadi fabrics from a competitive lot for optimal comfort is a challenging job, which has not been addressed so far by any researcher. The purpose of this study is to present one such selection problem using the multi-criteria decision-making (MCDM) technique, a popular branch of operations research, which can handle almost any decision problem involving a finite number of alternatives and multiple decision criteria.Design/methodology/approachTwo widely popular methods/exponents of MCDM, namely, analytic hierarchy process (AHP) and multiplicative analytic hierarchy process (MAHP) have been deployed in this study for ranking a competitive lot of 15 Khadi fabrics and selecting the best alternative for optimal summer comfort based on three comfort attributes, namely, drape coefficient, thermal insulation value and air permeability.FindingsBoth the approaches yield a similar ranking pattern with Spearman’s rank correlation coefficient of 0.9857, Khadi fabric K1 achieving Rank 1 (best in terms of optimal comfort) and sample K6 acquiring Rank 15 (worst choice). Two-phase sensitivity analyses were performed subsequently to demonstrate the stability of the two approaches: sensitivity analysis by changing weightage levels of the criteria and sensitivity analysis in dynamic decision conditions by changing the elements of the initial decision matrix. During sensitivity analyses, no occurrence of rank reversal is observed for the best and worst alternatives in either of the two approaches. This corroborates the robustness of the two models.Practical implicationsKhadi fabrics are widely acclaimed for their intrinsic comfort properties for both summer and winter. Although the popularity of Khadi fabrics is increasing day by day, this domain is under-researched, and hence, needs to be explored further. The present approach demonstrates how the MCDM technique can serve as a useful tool for ranking the available Khadi fabrics in terms of optimal comfort in summer. The same approach can be extended to other domains of the textile industry, in general, as well.Originality/valueThis study is the first-ever theoretical approach/research on the selection of Khadi fabrics for optimal summer comfort using the MCDM tool. Another novelty of the present study is that the efficacy of AHP and MAHP approaches, in this study, has been validated through a two-phase sensitivity analysis. This validation part has been ignored in most of the hitherto published applications of AHP and MAHP in other domains.

Applying analytic hierarchy process (AHP) to identify decision-making in soybean supply chains: a case of Mato Grosso production

Abstract: This paper aims to identify and analyze the factors that influence the decision of Mato Grosso’s farmers to produce soybean using the Analytic Hierarchy Process (AHP). We found evidence that decision-making of soybean production is related to rural production aspects such as climate, financing, cost of inputs, and soil quality rather than marketing and logistics. The novelty of this paper is the empirical analysis of the decision-making in agricultural production using AHP. The decision model was created and tested considering 21 farmers and 19 experts linked to the soybean production. Three different scenarios were considered: farmers' view, experts' view, and combined view. Our findings indicate that farmers and experts agree with rural aspects are predominant in the decision to plant soybean. Moreover, logistics have been used as an important flag of soybean competitiveness on international trade by soybean stakeholders in Brazil. However, our results show that logistics impact in the soybean decision-making process is low. Due to data limitation access, this study focuses only on Mato Grosso. However, this study has an exploratory character and presents empirical results that may help to understand soybean production over the country.

Multi-criteria decision-making approach for selecting a structural system of an industrial facility

Abstract Selection of an appropriate structural system for an industrial facility is a difficult task for decision makers since it is the essential component, and it is hard to satisfy the owner's demands as well as the legal requirements. There are many conflicting preferences that have to be considered to assess the performance of the structural system alternatives. Decision support systems (DSSs) such as multi-criteria decision-making (MCDM) methods are useful in making an objective and rational choice. It is important to use MCDM methods in order to analytically evaluate different factors affecting the structural system selection. To address these challenges, the selection of the structural system of an industrial facility project in Turkey was carried out by applying Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) MCDM methods. Eight evaluation criteria were determined for the selection process within the scope of the study, which are project cost, project duration, project lifetime, labour and equipment requirement, recycling opportunities, resistance to environmental effects, suitability for installation and natural lighting needs. Prefabricated reinforced concrete (PRC), on-site reinforced concrete (RC) and steel structural system alternatives were evaluated according to each criterion by a survey study conducted by 193 civil engineer participants. Using the AHP and TOPSIS methods, it is determined that the most suitable alternative for industrial facilities is the steel structural framing system. The results were argued with the design team, and they confirmed that MCDM methods could be easily integrated in selecting the most appropriate structural system.

Application of analytic hierarchy process for prioritisation of drivers of fit manufacturing

Fit manufacturing is a competitive strategy that encompasses the characteristics of lean, agile and sustainable systems. Fit system enables organisations to improve competitive performance. In order to enable effective implementation of fit manufacturing, its drivers need to be analysed. This paper presents prioritisation of drivers of fit manufacturing using multi-criteria decision making (MCDM) tool. Analytical hierarchy process (AHP) is used as solution methodology. Twenty drivers are being considered in the study. Appropriate computations are done and the priority order of drivers is derived. The top three priority drivers are being derived. The practical implications are being highlighted.

Multi-criteria approach to adjust demand forecast for products: application of analytic hierarchy process

Paper aims Investigate whether the results of time series models can be adjusted with the AHP method towards a more assertive forecast. Originality Considering demand forecasting as a complex decision-making situation, this research investigated the use of the AHP as a complement to traditional forecasting methods. Research method This applied research employed, as main procedures, literature review and mathematical modeling. Main findings Two models were proposed that presented satisfactory results: model I reduced the forecast error by 16% in January, 25% in February, 37% in March, 3% in April, and 7% in May; model II reduced it by 17% in January, 21% in February, 29% in March, 2% in April, and 5% in May. Implications for theory and practice We conclude that the AHP has the potential to correct the results of time series in the textile industry by allowing the incorporation of quantitative and qualitative variables.

Application of Analytic Hierarchy Process in Selecting a State-Made Electronic Documentation Management System for Polish Municipalities

This paper considers the problem of selecting a state-made electronic document management system (EDMS) using the analytic hierarchy process (AHP) model. The problem of EDMS selection from two available variants is analysed and the selection criteria related are highlighted on the basis of the literature and the authors’ experience. Calculations related to pairwise comparisons and prioritisation between criteria and variants form the core of the paper. This problem is only applicable to municipalities in Poland that have implemented an older state-made system; based on pair-wise comparisons, retaining the older system is preferable to implementing the new state-made EDMS because of the lack of integration of the new EDMS with internal systems.

Application of analytical hierarchy process and integrated fuzzy-analytical hierarchy process for mapping potential groundwater recharge zone using GIS in the arid areas of Ewaso Ng'iro – Lagh Dera Basin, Kenya

The demand for freshwater has continuously increased in the arid areas of Ewaso Ng'iro – Lagh Dera basin, Kenya. This study aimed to and mapped areas of potential groundwater recharge in the basin by integrating factors that influence groundwater recharge using Analytical Hierarchical Process, and Fuzzy-Analytical Hierarchical Process in ArcGIS. The results of this study are presented in form of maps indicating the potential groundwater recharge zones. The zones are categorized as high, medium and low potential groundwater recharge zone, which were validated with the location of the fresh water boreholes. High groundwater recharge potential zones occur in the central part of the study area within the generally flat flood plains consisting of alluvium lithology. In contrast, low potential groundwater recharge zones occur in the southwestern part of the area within upland plains. The study can be helpful in the proper management of the groundwater resource.

Ranking Security of IoT-Based Smart Home Consumer Devices

Manufacturers of smart home consumer devices like home theatres, music players, voice-based assistants, smart lighting, and security cameras have widely adopted the Internet of Things (IoT). These devices pose a significant security risk to consumers because the devices are exposed to mobile applications and cloud-based services with known security vulnerabilities. Most current home consumer devices provide little or no information about the level of security they afford. Since most consumers are not tech-savvy, it is currently difficult for a consumer to make an informed decision about which consumer device model (e.g., smart television model) has the best security. Hence, consumers need an objective security ranking of each type (e.g., security cameras) of home consumer devices. This paper proposes a novel methodology to systematically build such security rankings for home consumer devices. The proposed methodology can be applied by utilizing data from any security assessment study. The paper discusses previous efforts in applying Analytic Hierarchy Process (AHP) to rank security risks in general. The paper also presents a systematic survey of security vulnerabilities of smart home consumer devices when viewed from an IoT lens. Using the proposed methodology, a case study, employing an AHP model for ranking commonly used home consumer devices including home theatres, security cameras, smart lighting, smart speakers, video surveillance, smart switches, home automation systems, home security systems, smart routers, wireless doorbell cameras, and home audio systems, was developed. Relative security rankings for each type of consumer device were derived from the AHP model. According to the AHP model, network security was the primary driver of smart home device security with a priority of 0.6893 while application security had the least priority of 0.0591. Critical Vulnerabilities were the most important for device security (priority=0.4397), Man-in-The-Middle attacks for network security (priority=0.2019), exploitable services for cloud security (priority=0.26), and sensitive data for application security (0.7626). The AHP model was internally consistent (Consistency Ratio < 0.1). Sensitivity analysis showed that the AHP model was robust against pairing assumptions.

A supplier selection decision model using multi-criteria decision analysis in a small manufacturing company

Industry 4.0 and digitalization increasingly requires managers to make decisions in shorter time frames and at a higher level of accuracy. Among the many decision-making tools to help managers are multi-criteria decision-making methodologies (MCDM) such as Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP). The aim of this paper is to develop a MCDM hierarchical model with specific attributes of AHP/ANP to aid the decision-making process of buying capital spare parts from different suppliers. The paper is based on a case study of the comparative application of AHP and ANP approaches in a manufacturing company that develops and produces parts. We consider the decision involving 3 suppliers of a capital spare part (SP) with 3 decision makers inherent in the process. For this model, 6 attributes were grouped into 2 hybrid criteria. The results obtained through the decision process using the AHP and ANP are then compared and discussed.