Analytic Hierarchy Process Weight Research Articles

Ranking of MUDA using AHP and Fuzzy AHP algorithm

An analytical approach to the lean waste reduction and classification may have a significant influence on Industrial environment. In order to reduce the lean waste and to find the suitable solutions, waste identification is needed. Analytical Hierarchy Process (AHP) is the one of the way to segregate among the seven types of waste. But Fuzzy AHP is a synthetic extension of classical AHP method when the fuzziness of the decision maker is considered. In this paper analysis of AHP and Fuzzy AHP for the lean waste identification model has been presented. To accredit the proposed model a questionnaire is circulated to 30 number of companies in an international exhibition IMTEX 2015 conducted at Bangalore in India. Mostly multinational companies have participated in the international exhibition in which majority of the respondents belong to automobile industries. Initially AHP is used for determination of weights of lean waste but Fuzzy AHP is better choice to prioritize weights of the various types of lean waste.Both AHP and Fuzzy AHP results are analyzed and compared based on the results. Identification and elimination of the major lean waste leads to productivity improvement.

Set pair analysis for karst waterlogging risk assessment based on AHP and entropy weight

Abstract Karst waterlogging is a natural disaster that occurs frequently and it adversely affects the social and economic development of affected areas. An analysis of the causes of karst waterlogging with respect to climate and topography can serve as a foundation for disaster assessment and prevention. In this study, a karst waterlogging risk assessment indexing system was established. The system was based on a comprehensive analysis of risk factors, including the severity of the disaster and the vulnerability of the affected area. DeBao County in GuangXi was used as the study area. Nine risk indicators were chosen as evaluation indexes and combination weights were divided into subjective and objective weights based on the analytic hierarchy process (AHP) and entropy weight. A geographical information system (GIS) was applied to help with the calculations of the set pair analysis (SPA) and to pile up the layers of the evaluation indicators. Then, a risk rating map was drawn using GIS techniques. The results showed that the high risk locations were mainly distributed in the center of DeBao County; therefore, the map could be used as reference for the prevention and management of karst waterlogging risk.

Establishment of an Evaluation Model for Asphalt Pavement Preventive Maintenance Based on Improved EW-AHP

The evaluation methods for asphalt pavement preventive maintenance both local and abroad are investigated in this study. A comprehensive evaluation model that combines the evaluation index of pavement and material performance in domestic technical specifications and that considers the lack of weight allocation method for evaluation indices is proposed for the preventive maintenance of asphalt pavement. On the basis of the combination of practical engineering experiences, the expert scoring method, and experimental testing data, the model utilizes a new method, i.e., the improved entropy weight-analytic hierarchy process, to calculate the comprehensive weight coefficients of various evaluation indices and to evaluate the effect of preventive maintenance. The preventive maintenance engineering of highway asphalt pavement in Zhangjiakou is used as an example. Results show that the model is feasible. Moreover, the results can provide technical support for the application of preventive maintenance measures to asphalt pavement.

Multi objective optimization using different methods of assigning weights to energy consumption responses, surface roughness and material removal rate during rough turning operation

The present research work focuses on simultaneous optimization of prime energy consumption responses, surface roughness and material removal rate for sustainable machining operations. The experiments were conducted on rough turning of EN 353 alloy steel with multi-layer coated tungsten carbide insert. The effect of input parameters: nose radius, cutting speed, feed rate and depth of cut along with their interactions were studied on the response parameters viz. power factor (PF), active power consumed by the machine (APCM), active energy consumed by the machine (AECM), energy efficiency (EE), surface roughness (Ra) and material removal rate (MRR). The Taguchi’s L27 orthogonal array had been used for design of experiments by using Minitab 16 software. The weights of importance to the responses were assigned by Equal, Analytical Hierarchy Process (AHP) and Entropy weights method. The multi performance composite index (MPCI) was obtained by Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method and was optimized with Taguchi method. The results showed that the MPCI with these three different weight criteria had different optimum control factor levels. At optimal turning parameters of MPCI using AHP weights, Equal weights and Entropy weights, there was an improvement in MPCI of 319.72%, 45.38% and 9.02% respectively compared to turning parameters in common use. The depth of cut was found to be a vital parameter for MPCI with AHP weights and nose radius for MPCI with Equal and Entropy weights. Hence the choice of method of assigning weights of importance to the responses and even the optimization method plays important role in decision making in multi objective optimization.

Spatial distribution of rainstorm hazard risk based on EW-AHP in mountainous scenic area of China

ABSTRACTRainstorm hazards seriously affect the lives of residents and activities of tourists in rainstorm harder-hit scenic areas. The assessment of rainstorm hazard risk has a great significance in the area. Based on the disciplines of geography and tourism, an assessment system has been constructed by using the Entropy Weight-Analytic Hierarchy Process and exponential model. Finally, the Huayang Ancient Town Scenic Area in China has been taken as study area, and its rainstorm hazard risk and spatial distribution have been evaluated. The results indicate the following: The rainstorm hazard risk areas are mainly concentrated along rivers, valleys, or roads; The specific spatial distributions are: rainstorm hazard risk of the Huayang Old Streets is high, that of the Red Cliff Valley and both sides of the Mandarin Duck River are higher, that of the Golden Monkey Valley and the Macaque Park are lower, that of the Tangluo Ancient Road is low, and the risks of other areas are medium; The main influencing factors of rainstorm hazard risk are elevation, terrain, gap and width of river, distance to river, building density, tourist flow and tourism activity; People's awareness, system of monitoring and early warning, emergency plan, facilities and equipment for rainstorm hazard prevention and mitigation need to be continuously improved.

Spatially explicit sensitivity and uncertainty analysis for multicriteria-based vulnerability assessment

This research analyses the application of spatially explicit sensitivity and uncertainty analysis for GIS (Geographic Information System) multicriteria decision analysis (MCDA) within a multi-dimensional vulnerability assessment regarding flooding in the Salzach river catchment in Austria. The research methodology is based on a spatially explicit sensitivity and uncertainty analysis of GIS-CDA for an assessment of the social, economic, and environmental dimensions of vulnerability. The main objective of this research is to demonstrate how a unified approach of uncertainty and sensitivity analysis can be applied to minimise the associated uncertainty within each dimension of the vulnerability assessment. The methodology proposed for achieving this objective is composed of four main steps. The first step is computing criteria weights using the analytic hierarchy process (AHP). In the second step, Monte Carlo simulation is applied to calculate the uncertainties associated with AHP weights. In the third step, the global sensitivity analysis (GSA) is employed in the form of a model-independent method of output variance decomposition, in which the variability of the different vulnerability assessments is apportioned to every criterion weight, generating one first-order (S) and one total effect (ST) sensitivity index map per criterion weight. Finally, in the fourth step, an ordered weighted averaging method is applied to model the final vulnerability maps. The results of this research demonstrate the robustness of spatially explicit GSA for minimising the uncertainty associated with GIS-MCDA models. Based on these results, we conclude that applying the variance-based GSA enables assessment of the importance of each input factor for the results of the GIS-MCDA method, both spatially and statistically, thus allowing us to introduce and recommend GIS-based GSA as a useful methodology for minimising the uncertainty of GIS-MCDA.

An Integrated Decision-Making Model for Transformer Condition Assessment Using Game Theory and Modified Evidence Combination Extended by D Numbers

The power transformer is one of the most critical and expensive components for the stable operation of the power system. Hence, how to obtain the health condition of transformer is of great importance for power utilities. Multi-attribute decision-making (MADM), due to its ability of solving multi-source information problems, has become a quite effective tool to evaluate the health condition of transformers. Currently, the analytic hierarchy process (AHP) and Dempster–Shafer theory are two popular methods to solve MADM problems; however, these techniques rarely consider one-sidedness of the single weighting method and the exclusiveness hypothesis of the Dempster–Shafer theory. To overcome these limitations, this paper introduces a novel decision-making model, which integrates the merits of fuzzy set theory, game theory and modified evidence combination extended by D numbers, to evaluate the health condition of transformers. A four-level framework, which includes three factors and seventeen sub-factors, is put forward to facilitate the evaluation model. The model points out the following: First, the fuzzy set theory is employed to obtain the original basic probability assignments for all indices. Second, the subjective and objective weights of indices, which are calculated by fuzzy AHP and entropy weight, respectively, are integrated to generate the comprehensive weights based on game theory. Finally, based on the above two steps, the modified evidence combination extended by D numbers, which avoids the limitation of the exclusiveness hypothesis in the application of Dempster–Shafer theory, is proposed to obtain the final assessment results of transformers. Case studies are given to demonstrate the proposed modeling process. The results show the effectiveness and engineering practicability of the model in transformer condition assessment.

GIS based landslide susceptibility mapping of northern areas of Pakistan, a case study of Shigar and Shyok Basins

ABSTRACTThis study presents the use of geographical information system (GIS) datasets and methods to investigate landslide susceptibility in the rugged mountainous terrain of Shigar and Shyok Basins in northern areas of Pakistan. Study area is situated in Karakorum mountainous region where catastrophic landslides occur frequently and pose a serious threat to local living conditions. Landslide susceptibility index maps were prepared by combining four main indicators groups: (1) human induced parameters, which contain Landsat 8 imagery and distance from roads; (2) topographical parameters, which include slope, aspect and plan curvature; (3) hydrological parameters, which contain stream power index, topographic wetness index and distance from drainage and (4) geological parameters, which consist of lithology and distance from major thrusts and faults. These layers were prepared in GIS environment, and analytical hierarchy process (AHP) based heuristic approach was adopted to generate final landslide susceptibility map for this preliminary regional level landslide hazard study. Three different susceptibility zones have been identified in the region. AHP weights with 0.04 consistency ratio were used in the preparation of final map. The final landslide susceptibility map of the study area indicates that the low, moderate, and high landslide susceptibility classes are respectively covering 23.2% (4745 km2), 45% (6737 km2), 23.2% (3444 km2) when distance from roads, distance from drainage and distance from major thrusts and faults parameters were not incorporated in the analysis. Including distance from roads, distance from drainage and distance from major thrusts and faults parameters layers to the final landslide susceptibility analysis shows that moderate susceptibility class is the predominant landslide susceptibility category covering 88% (13,412 km2) of the study area characterized by steep slopes (30°–45°), low positive plan curvature (0–1) and weak lithology.

Research on the water-inrush risk of coal floors based on Fisher-evaluation and AHP

There are many factors that influence floor water-inrush. Based on the widely collected data of floor water-inrush in China, the evaluation factors in this paper consist of water pressure, aquifer type, aquiclude thickness, floor failure depth and fault throw. These are used to build a single Fisher evaluation model and a Fisher evaluation with weighting model of an analytic hierarchy process (AHP). By comparision, through AHP weighting value, the interclass distribution of the data in the Fisher model is relatively more concentrated than the single Fisher evaluation method. It would produce higher reliability and more extensive application value.

A COMPARATIVE STUDY OF AHP, ELECTRE III & ELECTRE IV BY EQUAL OBJECTIVE & SHANNON’S ENTROPY OBJECTIVE & SAATY’S SUBJECTIVE CRITERIA WEIGHTING IN A PRIVATE SMALL HYDROPOWER PLANTS INVESTMENTS SELECTION PROBLEM

<p>Private small hydropower plant investments are more challenging than medium and large private hydropower plant investments when considering engineering analysis. One of the necessary tasks is the selection of the most appropriate private small hydropower investment amongst several alternatives. Brokerage, consultancy and private investor activities are a few examples of these kinds of real world activities. There are many multi-criteria decision making (MCDM) or multiple-criteria decision analysis (MCDA) methods, and different researchers prefer different methods This research study investigates three methods at once for the same problem: Analytic Hierarchy Process (AHP), Elimination and Choice Translating Reality (ELECTRE) III and ELECTRE IV. A comparative investigation is conducted on one simple unique selection model for all three methods. This unified model has seven objective factors (catchment area, project runoff, net head, flow rate, firm energy, secondary energy, investment cost). An additional comparison is also made on the criteria weighting amongst equal objective, Shannon’s Entropy objective and Saaty’s subjective criteria weighting. The simplistic unified model is structured in three levels. There are seven alternatives in the pre-development investment stage. The Super Decisions software and the ELECTRE III-IV software are implemented in this study. The pairwise comparisons of factors results in an inconsistency value of 0,09511 which is 7<sup>th</sup> in the Saaty's AHP weighting. The Shannon’s Entropy objective weighting represents a difference in the rate of the expert decision maker’s evaluations ranging between -67% and 671%. The equal weighting represents a rate change between -64% and 626%. Both approaches can't represent human judgments (here only one expert decision maker) well in this model. Fortunately, the same alternative (Alternative 3) ranks first. These findings promise that further studies on this subject can give some clues for the development of an autonomous computer based intelligent decision support system. Some observed pros and cons of these methods are also presented in this study. The observations and critical issues are presented during modeling, application, evaluation and analysis to help researchers, consultants, and readers in the small hydropower investments research and practical fields. </p>

Green supplier selection using an AHP-Entropy-TOPSIS framework

Purpose – This paper aims to focus on development of a green supplier selection model using an index system based on a combination of traditional supplier and environmental supplier selection criteria. Strategies that balance economic and environmental performance are increasingly sought after as enterprises that increasingly focus on the sustainability of their operations. Green supply chain management (GSCM) in particular, enables the integration of environmentally friendly suppliers into the supply chain to be systematised to fit with specific environmental regulations and policies. More persuasively, GSCM allows enterprises to improve profits whilst lowering impacts on the global environment. Design/methodology/approach – A two-phase survey approach was adopted for the research. For the first phase, semi-structured interviews with senior management representatives of the case company – a Chinese-based electronic machinery manufacturer – were used to determine green supplier selection criteria. For the second phase, a two-part questionnaire survey was undertaken, the first part providing the data for an analytic hierarchy process (AHP) analysis of the first-phase criteria and the second with collecting data for an Entropy weight analysis. The resultant AHP and Entropy weights were then combined to form compromised weights – which, using technique for order preference by similarity to the ideal solution (TOPSIS) methodology, were translated into preferential rankings of suppliers. Findings – Senior managers were found to rank traditional criteria more highly than environmental alternatives – the implication being that for the company, concerned, it may take some time before environmental awareness is fully assimilated into GSCM practice. Originality/value – The paper moves us a significant step closer to the application more widely, of innovative AHP-Entropy/TOPSIS methodology to real-world SCM problems.

Adjustment comparison of veranda effect on building shadow area in semi-arid and moderate climates

This research was conducted to assess the performance of horizontal shading device on the building shadow area in two different climates of Iran. The case studies were two holy shrines in Shiraz and Savadkouh (semi arid climate and humid and moderate climate respectively) and were prioritized by Analytical Hierarchy Process weights. The solar angles and shadow area were derived and compared accordingly. The results showed that the shadow on the beneath wall of the lower latitude case study (Shiraz: 29°33′N) was 48.21% in January and 100% in July, and the parallel ratio for Savadkouh was 26.1% in January and 97.22% in July. Through comparison of the monthly shadow area on wall in July with that in January in both climates, the Shiraz and Savadkouh ratios were found to be 2.78 and 4.79, respectively, which indicated that shadow areas in summer were more than those in winter. Therefore, the shadow could cause more outdoor thermal comfort in winter and summer in both climates.

Sensitivity and Uncertainty Analysis Approach for GIS-MCDA Based Economic Vulnerability Assessment

This research aims to employ a novel methodology for modelling uncertainty in the GIS environment. The spatially explicit sensitivity and uncertainty analysis was applied on Multicriteria Decision Analysis (MCDA) for an economic vulnerability assessment within the Salzach Basin. The main objective of this research is to demonstrate how a unified approach of uncertainty and sensitivity analysis can be applied to minimize the associated uncertainty within an economic vulnerability assessment. In order to achieve this objective, the following methodology, composed four steps, was applied: (1) computation of criteria weights using Analytic Hierarchy Process (AHP); (2) Monte Carlo Simulation was applied for computing the uncertainties associated with AHP weights; (3) the Global Sensitivity Analysis (GSA) was employed in the form of the model-independent method of output variance decomposition, in which the variability of vulnerability maps is apportioned to every criterion weight, generating one first-order (S) and one total-effect (ST) sensitivity index map per criterion weight; and (4) an Ordered Weighted Averaging method was applied for producing vulnerability maps. The results of this research demonstrated the robustness of spatially explicit GSA for minimizing the uncertainty associated with GISMCDA models. According to the achieved results, we conclude that applying the variance based GSA leads to a spatial and statistical assessment of the importance of each input factor on the outcome of the GIS-MCDA method, which allows us to introduce and recommend GIS based GSA as a useful methodology for minimizing uncertainty of GISMCDA.

Effectiveness Evaluation Analysis of Weapon Equipment System Based on Weighted Gray Relational Degree

In order to solve the diverse problems of effectiveness evaluation of current weapon equipment systems, which are multiple hierarchies, multiple factors and different relational degree among the factors of system, the shortage of Analytic Hierarchy Process (AHP) and traditional Gray Relational Degree is analyzed and a new evaluation method of the weighted gray relational degree is proposed in this paper. This method is used for evaluating weapon equipment systems by combining AHP with Gray Relational Degree. Finally, feasibility and effectivenessof Weighted Gray Relational Degree for multiple hierarchies and multiple factors weapon equipment systems can be proved by a case analysis.The result showed that Weighted Gray Relational Degree would be more reliable than single weight of AHP. And Weighted Gray Relational Degree can solve the weakness of traditional Gray Relational Degree which isunable to effectively evaluate the multiple hierarchies and multiple factors of weapon equipment systems.

REVIEW OF DIFFERENT METHODS FOR DERIVING WEIGHTS IN THE ANALYTIC HIERARCHY PROCESS

The Analytic Hierarchy Process (AHP) is a multi-criteria decision making technique developed to solve both single and group decision making problems. In AHP, the approach that has been proposed by Saaty to derive priority weights by using the eigenvector method (EVM) had it's drawbacks immediately after its publication in 1980's, and since then various methods were developed as alternatives. This paper presents an extensive review of various methods for deriving priority weights in AHP, including group decision making, and focuses on comparison of each method with the EVM. The results of the comparison reveal that each method has its advantages and disadvantages, and should be used depending on the application. http://dx.doi.org/10.13033/ijahp.v6i1.226

A COMBINED FUZZY MCDM APPROACH FOR IDENTIFYING THE SUITABLE LANDS FOR URBAN DEVELOPMENT: AN EXAMPLE FROM BANDAR ABBAS, IRAN

This study aims at identifying the suitable lands for urban development in Bandar Abbas city based on its real world use regarding specific criteria and sub-criteria. The city of Bandar Abbas is considered as the most important commercial and economic city of Iran. It is also considered as one of the major cities of Iran which has played a pivotal role in the country's development and progress in recent years especially after the end of Iran-Iraq war owing to its embracing the country's main commercial ports. This process has caused the immigration rate into the city to rise significantly over the past 20 years. Thus, the development of the city is meanwhile considered as a high priority. Bandar Abbas city does not have a rich capacity for growth and development due to its special geographical situation being located in coastal border. Among the limitations placed in the city's development way, natural limitations (heights and sea shore) in the northern and southern parts of the city and structural limitations (military centers) in the east and west sides of the city may be referred. Therefore, identifying the suitable lands for urban development within Bandar Abbas city limits is becoming an essential priority. Therefore, different quantitative and qualitative criteria have been studied in order to select and identify these lands. The structures of qualitative criteria for most parts involve ambiguities and vagueness. This leads us to use Fuzzy logic in this study as a natural method for determining the solutions for problems of Multi-criteria decision making (MCDM). In the current research, a combination of MCDM methods has been presented for analysis. To assignee weights of the criteria Fuzzy AHP (analytic hierarchy process) is used for land selection and Fuzzy TOPSIS (method for order priority by similarity to ideal solution) is utilized to choose the alternative that is the most appropriate through these criteria weights. The sensitivity analysis of the results is included in the research.

A COMBINED FUZZY MCDM APPROACH FOR IDENTIFYING THE SUITABLE LANDS FOR URBAN DEVELOPMENT: AN EXAMPLE FROM BANDAR ABBAS, IRAN

This study aims at identifying the suitable lands for urban development in Bandar Abbas city based on its real world use regarding specific criteria and sub-criteria. The city of Bandar Abbas is considered as the most important commercial and economic city of Iran. It is also considered as one of the major cities of Iran which has played a pivotal role in the country's development and progress in recent years especially after the end of Iran-Iraq war owing to its embracing the country's main commercial ports. This process has caused the immigration rate into the city to rise significantly over the past 20 years. Thus, the development of the city is meanwhile considered as a high priority. Bandar Abbas city does not have a rich capacity for growth and development due to its special geographical situation being located in coastal border. Among the limitations placed in the city's development way, natural limitations (heights and sea shore) in the northern and southern parts of the city and structural limitations (military centers) in the east and west sides of the city may be referred. Therefore, identifying the suitable lands for urban development within Bandar Abbas city limits is becoming an essential priority. Therefore, different quantitative and qualitative criteria have been studied in order to select and identify these lands. The structures of qualitative criteria for most parts involve ambiguities and vagueness. This leads us to use Fuzzy logic in this study as a natural method for determining the solutions for problems of Multi-criteria decision making (MCDM). In the current research, a combination of MCDM methods has been presented for analysis. To assignee weights of the criteria Fuzzy AHP (analytic hierarchy process) is used for land selection and Fuzzy TOPSIS (method for order priority by similarity to ideal solution) is utilized to choose the alternative that is the most appropriate through these criteria weights. The sensitivity analysis of the results is included in the research.

The Art of Integrated GIS/AHP for Siting Landfill: A Review

This article reviewed selected works on how decision makers (DMs) utilize integrated geographic information system (GIS)/analytical hierarchy process (AHP) tools to analyze land suitability for sanitary landfill sites as part of regional planning. We analyzed the hierarchy process of certain pervious works to facilitate better understanding. The innovative work of Siddiqi et al. in 1996 highlighted the advantages of integrating AHP in GIS software and reviewed some limitations. The present paper explained the background study on multi-criteria decision analysis/aid (MCDA) so-called multi-criteria decision makers (MCDM) in conjunction with the advantages of GIS as a new remedy for utilizing the AHP weights of the decision makers. For this study we often use the term MCDA and MCDM.

On Fuzzy Priority Weights of AHP for Double Inner Dependence Structure

The Analytic Hierarchy Process (AHP) is very popular method in decision making process, and its inner dependence extension is used for cases in which criteria or alternatives are not independent enough. Calculations and compositions of weights are very important steps in it, however using the AHP (inner dependence AHP) may cause results losing reliability because the comparison matrix is not necessarily sufficiently consistent. In such cases, fuzzy representation for weighting criteria or alternatives using results from sensitivity analysis is useful. In the previous papers, we defined local weights of criteria and alternatives for inner dependence AHP via fuzzy sets. In this paper we deal with overall weights of alternatives for double inner dependence structure AHP (among criteria and alternatives respectively). We propose fuzzy weights and two kinds of compositions. The compositions of weights depends if there are inconsistency in one level or not. Their results show the fuzziness of double inner dependence structure AHP in different way.

Multiple attribute network selection algorithm based on AHP and synergetic theory for Heterogeneous Wireless Networks

It is a hot issue in communication research field to select the best network for Heterogeneous Wireless Networks (HWNs), and it is also a difficult problem to reduce the handoff number of vertical handoff. In order to solve this problem, the paper proposes a multiple attribute network selection algorithm based on Analytic Hierarchy Process (AHP) and synergetic theory. The algorithm applies synergetics to network selection, considering the candidate network as a compound system composed of multiple attribute subsystems, and combines the subsystem order degree with AHP weight to obtain entropy of the compound system, which is opposite the synergy degree of a network system. The greater the synergy degree, the better the network performance. The algorithm takes not only the coordination of objective attributes but also Quality of Service (QoS) requirements into consideration, ensuring that users select the network with overall good performance. The simulation results show that the proposed algorithm can effectively reduce the handoff number and provide uses with satisfactory QoS according to different services.