Analytic Hierarchy Process Matrix Research Articles

Selection of Recommended Marketing Strategy of Arrowroot Cereal at PT Serela Prima Nutrisia Using Analytical Hierarchy Process

PT Serela Prima Nutrisia is a company engaged in the arrowroot (Maranta Arundinacea)-based processing product. (1) This research aimed to identify and analyze alternative strategies that could be applied in Oriflakes marketing activities and (2) to identify the company’s marketing strategy that could be recommended according to the segmentation, targeting, and positioning. This research used a descriptive approach. The location determination method used case studies whereas the determination of the respondents used a purposive method. Types of data used in this research were primary and secondary data. The data collection methods used in this research were observation, interviews, documentation, recording, and questionnaires. The analytical techniques used in this research were Descriptive Analysis, Internal and External Factors Matrix, IE Matrix (Internal External), and AHP (Analytical Hierarchy Process). The results from this research showed that the marketing mix applied by the company were product, price, promotion, place, and the STP concept, which were segmentation, targeting, and positioning. The results from the IE matrix showed that the company position was on hold and maintain. The results of the AHP matrix showed that the highest socre was obtained on the product development strategy. An alternative strategy recommended for the company was a product development strategy.

Research on the Design of Surgical Auxiliary Equipment Based on AHP, QFD, and PUGH Decision Matrix

To improve the efficiency of medical staff in surgical operations and meet the physiological and psychological needs of surgeons, nurses, and patients during the operations, surgical auxiliary equipment is designed. This paper builds a design research model based on AHP (analytic hierarchy process), QFD (quality function deployment), and Platts conceptual decision matrix (PUGH decision matrix). Firstly, the user requirements are weighed through AHP analysis, and the design elements are prioritized based on the weight values. Then, QFD is used to analyze the design features of surgical auxiliary equipment from the aspects of structure, function, and shape, and a house of quality is established to get the significance of design features. Finally, the PUGH decision matrix is constructed to screen and evaluate multiple schemes, and the optimal design scheme is obtained. From the perspective of user requirements and product design characteristics, the significance of design elements is analyzed and calculated, which guides the design practices to complete the innovative design of surgical auxiliary equipment. The combination of AHP, QFD, and PUGH decision matrices are introduced into the innovative design of surgical auxiliary equipment, effectively avoiding subjective factors in product design, improving the scientific nature of the design, and providing new methods and ideas for the design and research of surgical auxiliary equipment and similar products.

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.

Landslide’s analysis and Hazard mapping based on ANALYTIC HIERARCHY PROCESS (AHP) using GIS, in Lawas, Sabah-Sarawak

This research was conducted to establish a landslides hazard map in a district called Lawas in Malaysia’s Sabah–Sarawak region using the AHP (Analytic Hierarchy Process) methods. Several landslides conditioning factors in the area were identified and used to build the AHP matrix. The landslides triggering factor(s) of the area was observed to be rainfall based on previous investigation reports for landslides in the regions and the landslides history records. The weightage values for the conditioning factors were assigned considering the contributions of each factor as observed from the spatial data analysis. These landslides’ conditioning factors were; slope, aspect, soil type, SPI, STI, rainfall intensity, elevation, Profile curvatures, and lithology. Satellite images constituted the primary part of the database used for the AHP analysis. GIS tools such as ArcMap were also utilized to read and analyze the remotely sensed data for the analysis. The susceptibility or hazard map was finally developed using ArcMap software through weighted overlay in a GIS (Geographic Information System) platform. The hazards map was later formulated by reclassifying the landslides susceptibility maps. Overall, the study revealed that all factors collected were very influential to landslides occurrence in the study area and that the AHP method was also discovered to be effective.

An Inner Dependence Analysis Dynamic Decision-Making Framework

During the last decade, with the rapid development of information technology, the immense volume of data poses a challenge to decision-makers. We use a combined dynamic decision-making approach based on the analytic hierarchy process (AHP) to select the best supplier. In this paper, we discuss the interaction between criteria that can lead to expanding our proposed dynamic framework to consider the inner dependencies among criteria. The main contributions are: (1) identifying the most important criteria of supplier selection in a steel bar manufacturer in Taiwan; (2) proposing a simple and rapid analysis of the appropriate supplier selection evaluation framework; and (3) using the AHP and transformation matrix to present the inner dependence among the criteria.

Neutrosophic Completion Technique for Incomplete Higher-Order AHP Comparison Matrices

After the recent establishment of the Sustainable Development Goals and the Agenda 2030, the sustainable design of products in general and infrastructures in particular emerge as a challenging field for the development and application of multicriteria decision-making tools. Sustainability-related decision problems usually involve, by definition, a wide variety in number and nature of conflicting criteria, thus pushing the limits of conventional multicriteria decision-making tools practices. The greater the number of criteria and the more complex the relations existing between them in a decisional problem, the less accurate and certain are the judgments required by usual methods, such as the analytic hierarchy process (AHP). The present paper proposes a neutrosophic AHP completion methodology to reduce the number of judgments required to be emitted by the decision maker. This increases the consistency of their responses, while accounting for uncertainties associated to the fuzziness of human thinking. The method is applied to a sustainable-design problem, resulting in weight estimations that allow for a reduction of up to 22% of the conventionally required comparisons, with an average accuracy below 10% between estimates and the weights resulting from a conventionally completed AHP matrix, and a root mean standard error below 15%.

Assessing Liveable Cities for Older People in an Urban District in Turkey Using the Analytical Hierarchy Process

The key concepts availability and accessibility have been taken into consideration in urban studies as well as the health and social aspects of ageing. These terms are in close relation with the “active ageing”, “age-friendly city” and “liveable city” concepts. These concepts were created by the UN, the World Health Organization, and other institutions aiming to increase the quality of life of older individuals and to regulate their living environments in an optimal way for an active and independent life. Improving accessibility and availability of facilities for older people in urban areas is crucial to ensure that older people are able to meet their own needs as well as prevent their exclusion from society. The planning of cities that prevents the social exclusion of older people and provides an independent way of living is the main objective of the concept of liveable cities. From this point of view, this study aims to evaluate the existing opportunities in an urban area in the context of liveability. Out of the multi-criteria decision-making models, analytic hierarchy process (AHP) and geographic information systems (GIS) were therefore used in this research. Three main districts of Kepez, with the highest population of older individuals, have been chosen. According to the findings of the study, the weight of health services has the highest score compared to other criteria. The liveability scores and grading of the districts were obtained using the AHP matrix. In the study, it was concluded that a multi-criteria analysis could be carried out with quantitative data. The real land use and the close environment of the research area should also be considered in the evaluation process.

Optimizing the total-body skin exam: An observational cohort study

Total-body skin examinations (TBSEs) are commonly performed in clinical practice. There is limited research on best practices for performing a TBSE. To optimize the TBSE. We performed an observational cohort study by video recording 5 dermatology faculty and 5 residents conducting their regular TBSE on both a healthy male and female patient. Examination time, physician movements, patient movements, sequence of body parts examined, and body parts missed were analyzed by using an analytic hierarchy process matrix. Differences were evaluated by a t test of unequal variance. P values<.05 were deemed significant. We identified an optimal format for conducting a TBSE that is efficient and accurate. This study was conducted with only standard healthy examiners and patients, rather than individuals with a variety of physical or mental disabilities. The structure of the study was not hypothesis driven, and we assumed that the engineers observing the physicians performing the examination would identify the most optimal TBSE. Our results indicate that a standardized process of performing a TBSE minimizes the chance of missing a body area. This could also have implications on teaching a standardized TBSE to medical students, residents, and physicians.

A Fuzzy AHP Approach to Comparison of Grant Aid for ODA in Japan

Today, many companies contribute to Official Development Assistance (ODA). The details of ODA are publicised for each project, with contributions and companies listed on the company’s website. The objective of this paper is to evaluate these companies in terms of the best practices that characterise ODA donations in four fields: infrastructure, medical service, education and security. Analytic hierarchy process (AHP) is proposed by T. L. Saaty to evaluate uncertainty in decision problems. Using comparison matrices, the AHP can evaluate the extent of data fit to practical data. In fuzzy analytic hierarchy process (Fuzzy AHP), interval weights play a pivotal role and can be solved by linear programming. An approach to fuzzy AHPs is to estimate interval priorities on the items discussed. These interval weights are based on the concept of possibility and express the range of the possibility. The method employed by H. Tanaka is to minimise the range including the given data. The range of the possibility can be illustrated as the interval or width of calculated values. Similar to a conventional AHP model, the fuzzy AHP model has a hierarchical structure that is used to decide the priority of each alternative with the minimal evaluation width of each alternative. Saaty proposed that an AHP matrix should have a Consistency Index (C.I.) of less than 0.1, since theory suggests that C.I. should be satisfied. The fuzzy AHP Model can minimise such vagueness and uncertainty in the hierarchical structure used to evaluate alternatives.

Sparse and distributed Analytic Hierarchy Process

The Analytic Hierarchy Process (AHP) is a de-facto standard technique in centralized decision making. Consider a situation where there is a need to rank a set of elements or alternatives, based on their value or utility, of which we just know pairwise relative information, i.e., the ratio of their values. AHP proved an effective tool to retrieve the value of each element, being able to handle also relative information affected by distortions, subjective biases and intransitivity. A downside of AHP, however, is that it requires complete information, i.e., knowledge on all pairs. In this paper, we extend the applicability of the AHP technique to the case of sparse information, i.e., when only a limited amount of information is available, and such an information corresponds to an undirected connected graph. We complement our sparse framework by developing novel criteria and metrics to evaluate the degree of consistency of the data at hand. Moreover, exploiting the proposed framework, we also provide a distributed formulation of AHP in which a set of agents, interacting through an undirected graph, are able to compute their own values (e.g., for ranking or leader election purposes), by only knowing the ratio of their values with respect to their neighbors. To this end, we develop a novel algorithm to let each agent i compute, the dominant eigenvalue and the ith component of the corresponding eigenvector of the sparse AHP matrix. We conclude the paper with a simulation campaign that numerically demonstrates the effectiveness of the proposed approach.

Empirical Analysis of Barriers to Energy Efficiency in Small Scale Industrial Cluster

Objectives: This research work is conducted in small scale industries to highlight energy efficiency gap that has often been neglected from the analysis in manufacturing cluster. The study is done to evaluate - Intensity of Barrier (IOB), Easiness of Barrier Removal (EOB) and Impact of Barrier Removal (IBREE) on Energy Efficiency for the top four barrier-groups by using mathematical model based on Analytic Hierarchy Process (AHP). Methods/Statistical Analysis: The data for AHP matrix is collected through an online questionnaire sent to 180 respondents from the list of 330 industries selected randomly. The four barrier groups are selected based on various studies conducted on Barriers to energy efficiency in India and abroad. The total cluster population consists of 330 Small Scale Manufacturing units in Mohali district of Punjab. Considering the reliability of respondents, the confidence interval 0.20 and confidence level 95% is chosen respectively. The calculated sample size using these parameters is 22. Findings: The Results highlighted many important findings that inhibit the energy efficiency benefits is these cluster and affect degree of implementation. Policy and Regulatory Barrier followed by Personal&Informational Barrier having score value 0.36 and 0.24 respectively are found to be high-intensity Barriers that act as impediments to energy efficiency policies in manufacturing cluster. The Personal&Informational Barrier is easiest to remove whereas Policy and Regulatory Barrier is most difficult to remove barrier group according to AHP results. Application/Improvements: The analysis pointed out that if Policy and Regulatory Barrier is removed would result in significant chances of achieving energy efficiency in these clusters. An initiative from state government bodies in collaboration with field specific experts is necessary to formulate effective policies to address this barrier group. The Personal&Informational Barrier can be addressed through regular interactions with experts, training programs and behavior modification techniques.

Evaluasi dan Pengembangan Sistem Manajemen Rantai Pasok Bandeng Segar (Chanos chanos) di Kota Bekasi, Jawa Barat

Case study is conducted towards 12 SME milkfish processors in Bekasi, at which its raw materials are originated from Karawang Regency through a fresh milkfish supply chain. The potentcy of Karawang Regency as a milkfish producer does not guarantee continuous availability of the raw materials. The objectives of this study were: (1) To evaluate supply chain; and (2) To compile a priority strategy of fresh milkfish supply chain management in Bekasi, West Java. Data collection was conducted by purposive and snowball sampling techniques, starting from SME processors, retailers and collective traders in Bekasi, to milkfish farmers in Ciparage Jaya Village, Tempuran Sub-District, Karawang Regency. The study used descriptive analysis, evaluation by comparing the activities of the members of the supply chain with the existing standards, Strength, Weaknesses, Opportunities and Threats (SWOT) analysis and Analytic Hierarchy Process (AHP). The evaluation result showed there was gap between the activities of each supply chain member with the Indonesian National Standard (SNI) namely (1) implementation of GMP and SSOP by SME processors, (2) means of transport and storage of fresh fish by collective trader and retailer, (3) good aquaculture practices by farmer and (4) supply chain management by all members along the supply chain. Based on the SWOT and AHP matrix analyses, the development strategies of supply chain by actor was (1) the formation of raw material procurement network and marketing network by SME processor (0.326); (2) the quality improvement of human resource by the government (0.249); (3) the formation of organizations by farmer (0.230), and (4) maintaining partnership in business procurement cost by collective trader (0.195).

USING MCDA AND GIS FOR LANDFILL SITE SELECTION: CENTRAL DISTRICTS OF ANTALYA PROVINCE

The aim of this study is to select new landfill sites in Antalya, Turkey which is the fifth biggest city according to the population, approximately 1.2 million. It is the first rank according to the population growth rate in Turkey. The city of Antalya is the touristic places and its climate is Mediterranean climate. Therefore, choosing landfill site is very crucial and it affects the future of the city. Existing landfill site will not be sufficient in near future. The study was implemented in the Aksu, Dosemealti, Kepez, Konyaalti, and Muratpasa districts in Antalya. The study area has almost 1980 km-square. Twelve parameters which are geology, fault lines, landslides, river, lake, elevation, slope, aspect, population, rain, road network, and temperature data were determined. These parameters were assessed using Analytical Hierarchy Process (AHP) method and the weights of criteria layers were computed. Then, the computed weights were checked by the consistency index and consistency ratio which were found as 0.12 and 8.5%, respectively. The consistency index for 12 parameters should be lower than 1.48 and the consistency ratio should be less than 10%. This means that the constructed AHP matrix is suitable for analysis. Finally, the most suitable areas for landfill were computed according to the weights achieved from AHP matrix. The results were obtained in a range between 0.39 and 0.90. When the obtained results were compared with the existing landfill site called Kizilli area, the AHP score was found as 0.62. Therefore, new landfill area(s) should be selected from the determined results.

USING MCDA AND GIS FOR LANDFILL SITE SELECTION: CENTRAL DISTRICTS OF ANTALYA PROVINCE

Abstract. The aim of this study is to select new landfill sites in Antalya, Turkey which is the fifth biggest city according to the population, approximately 1.2 million. It is the first rank according to the population growth rate in Turkey. The city of Antalya is the touristic places and its climate is Mediterranean climate. Therefore, choosing landfill site is very crucial and it affects the future of the city. Existing landfill site will not be sufficient in near future. The study was implemented in the Aksu, Dosemealti, Kepez, Konyaalti, and Muratpasa districts in Antalya. The study area has almost 1980 km-square. Twelve parameters which are geology, fault lines, landslides, river, lake, elevation, slope, aspect, population, rain, road network, and temperature data were determined. These parameters were assessed using Analytical Hierarchy Process (AHP) method and the weights of criteria layers were computed. Then, the computed weights were checked by the consistency index and consistency ratio which were found as 0.12 and 8.5%, respectively. The consistency index for 12 parameters should be lower than 1.48 and the consistency ratio should be less than 10%. This means that the constructed AHP matrix is suitable for analysis. Finally, the most suitable areas for landfill were computed according to the weights achieved from AHP matrix. The results were obtained in a range between 0.39 and 0.90. When the obtained results were compared with the existing landfill site called Kizilli area, the AHP score was found as 0.62. Therefore, new landfill area(s) should be selected from the determined results.

Landslide Susceptibility Mapping Using Analytical Hierarchy Process (AHP) in Tehri Reservoir Rim Region, Uttarakhand

Abstract: A comprehensive use of analytical hierarchy process (AHP) method in landslide susceptibility mapping (LSM) has been presented for rim region of Tehri reservoir. Using remote sensing data, various landslide causative factors responsible for inducing instability in the area were derived. Ancillary data such as geological map, soil map, and topographic map were also considered along with remote sensing data. Exhaustive field checks were performed to define the credibility of the random landslide conditioning factors considered in this study. Apart from universally acceptable inherent causative factors used in the susceptibility mapping, others such as impact of reservoir impoundment on terrain, topographic wetness index and stream power index were found to be important causative factors in rim region of the Tehri reservoir. The AHP method was used to acquire weights of factors and their classes respectively. Weights achieved from AHP method matched with the existing field conditions. Acceptable consistency ratio (CR) value was achieved for each AHP matrix. Weights of each factor were integrated with weighted sum technique and a landslide susceptibility index map was generated. Jenk’s natural break classifier was used to classify LSI map into very low, low, moderate, high and very high landslide susceptible classes. Validation of the susceptibility map was performed using cumulative percentage/success rate curve technique. Area under curve value of the success rate curve was converted to percentage validation accuracy and a reasonable 78.7% validation accuracy was achieved.

Prioritizing Food Security Indicators in Iran: Application of an Integrated Delphi/AHP Approach

Background: Monitoring of food insecurity is a critical issue for planners and policymakers in the public and private sectors in developing countries. Due to the multifactorial and multidimensional nature of food security and a lack of clarity concerning the causes, specific signs, and consequences of food insecurity, developing a reliable food security index is the major challenge related to monitoring food security. Objectives: The objective of this study was to identify the most appropriate indicators of food security at the provincial level in Iran through the application of an integrated approach including Delphi (classic Delphi) and analytic hierarchy process (AHP) from March to September 2013. Materials and Methods: The sample included 43 senior-level managers and experts at the national and provincial levels from different fields of related sciences; they were selected purposively as Delphi and AHP panel members based on the experts’ opinions and snowballing. In the first round of Delphi, out of 103 identified indicators, 38 were selected by the experts; the indicators were ranked in the second round. In the AHP study, 25 experts assigned weights in a pairwise comparison of the 20 indicators that had the highest priority based on the Delphi results. Using AHP matrix calculations, this list of indicators was ranked based on priority. Results: Out of 38 indicators identified in Delphi, 8 were related to the availability dimension, 14 were related to the access dimension, and 16 were related to the utilization dimension. Out of 20 indicators that were ranked in the AHP study, 6 indicators were related to availability, 7 were related to utilization, and 7 were related to access dimensions. However, the indicators related to availability had an overall higher rank compared to indicators related to access or utilization. Conclusions: This study identified and ranked 20 indicators as the most appropriate indicators of food security measurements at the provisional level in Iran.

Susceptibility Assessment of Shallow Landslides in Hulu Kelang Area, Kuala Lumpur, Malaysia Using Analytical Hierarchy Process and Frequency Ratio

Hulu Kelang is known as one of the most landslide susceptible areas in Malaysia. From 1990 to 2011, a total of 28 landslide events had been reported in this area. This paper compares two models as Analytical Hierarchy Process (AHP) and probability–frequency ratio (FR) methods for recognizing landslide susceptibility regions in the Hulu Kelang area. Eleven landslide influencing factors were considered to form the probability–FR and AHP matrix, i.e. lithology-weathering, land cover, curvature, slope inclination, slope aspect, drainage density, elevation, distance to lake and stream, distance to road and trenches, the Stream Power Index and the Topographic Wetness Index. The accuracy of the maps produced from the two models were verified using a receiver operating characteristics. The verification results indicated that the probability–FR model based on probabilistic analysis of spatial distribution of historical landslide events was capable of producing a more reliable landslide susceptibility map in this study area compared to AHP model. About 89 % of the landslide locations have been predicted accurately by using the FR map.

Spatial Decision Support System for Low-Income Families Relocation Tool for the Chicago, Illinois, Region

Housing relocation or housing mobility is not uncommon in the United States, with the average family relocating once every 6 years. As part of this process, individuals and families take into account a variety of factors. One of the important factors is that of transportation and its availability. Various researchers have studied the impact of transportation information on relocation choice. However, the need for a structured methodology that incorporates various factors, such as transportation, has been highlighted from a study of the current practice of relocation counseling. The objectives of this paper are threefold: (a) to develop an analytical hierarchy process to rank census tracts for relocation purposes of individuals, (b) to present a prototype of the spatial decision support system (SDSS) with an example, and (c) to evaluate the impact of relocation choice of individuals by using a spatially unconstrained approach. With data from the six-county northeastern Illinois region, the SDSS is developed and showcased with the help of a sample application. Two scenarios are tested for each respondent. The first is based on only housing criteria, and the second compares all criteria in the analytical hierarchy process matrix with each other. The improvements in travel time determined from the results of the two scenarios are compared, and the results are discussed to highlight the salient features of the decision support system.

Spatial Decision Support System for Low-Income Families

Housing relocation or housing mobility is not uncommon in the United States, with the average family relocating once every 6 years. As part of this process, individuals and families take into account a variety of factors. One of the important factors is that of transportation and its availability. Various researchers have studied the impact of transportation information on relocation choice. However, the need for a structured methodology that incorporates various factors, such as transportation, has been highlighted from a study of the current practice of relocation counseling. The objectives of this paper are threefold: (a) to develop an analytical hierarchy process to rank census tracts for relocation purposes of individuals, (b) to present a prototype of the spatial decision support system (SDSS) with an example, and (c) to evaluate the impact of relocation choice of individuals by using a spatially unconstrained approach. With data from the six-county northeastern Illinois region, the SDSS is developed and showcased with the help of a sample application. Two scenarios are tested for each respondent. The first is based on only housing criteria, and the second compares all criteria in the analytical hierarchy process matrix with each other. The improvements in travel time determined from the results of the two scenarios are compared, and the results are discussed to highlight the salient features of the decision support system.