Analytic hierarchy process model

Chapter 4 covers the site selection and site controlling phase. Consequently, it deals with the assessment of individual production sites based on primarily qualitative criteria. Alternative Multiple Attribute Decision Analysis methods are reviewed and a decision support model employing the Analytic Hierarchy Process, which can be used both for site selection problems and as a controlling tool to perform site portfolio rankings of entire production networks, is proposed. Experiences from application in industry are reported. 

The objective was to develop a site assessment model based on the Analytic Hierarchy Process that can be used both for site selection and site ranking/controlling purposes. While the different application situations to some extent require different criteria the intention was to develop a model as uniform as possible to achieve consistency in site strategy processes. 

Saaty TL, Vargas LG (2001) Models, Methods, Concepts Applications of the Analytic Hierarchy Process. Kluwer Academic Publishers, Boston et al. 

Basak, 1., and Saaty, T. (1993), Group Decision Making Using the Analytic Hierarchy Process, Mathematical and Corrtputer Modeling, Vol. 17, pp. 101-109. 

The Security incidents of purification plant are influenced by many factors. However, each factor can just reflect one side of the problem. In order to evaluate the safety level of the purification plant comprehensively, it is necessary to introduce indicators as much as possible in the evaluation model and follow an independent, comprehensive, comparable principle at the same time (SHENG et al. 2012, ZHOU et al. 2012). So this paper uses the Analytic Hierarchy Process (AHP) analysis and forms well-organized recursive node hierarchy structure, as shown in Figure 1. 

Based on the nature of issues and the overall objective to be achieved, analytical hierarchy process decomposes the issue into different constituent factors, and arranges the factors at different levels in accordance with their correlation and affiliation to form a multi-leveled analytical structure model, which ultimately boils the issue down to how to determine the relative important weights or priorities at the lowest level relative to the highest level. 

The analytic hierarchy process (SHP) to determine the index weight was used. By establishing the hierarchy model, to construct judgment matrix, hierarchical sorting and consistency check to confirm the weight. By designing the questionnaire, more than 50 invited experts to participate in the questionnaire, and calculate the survey results, the weights were obtained as show in Table 4. 

Braglia, M. Bevilacqua, M. 2000. Fuzzy modelling and analytical hierarchy processing as a means of quantifying risk levels associated with failure modes in production systems. Technology, Law and Insurance 5 125-134... 

Dagdeviren, M. Yuksel, I. 2008. Developing a fiizzy analytic hierarchy process (AHP) model for behaviour-based safety management. Information Sciences 178 1717-1733... 

Zhong, L. Youchao, S. 2007. Research on Maintainability Evaluation Model Based on Fuzzy Theory. Chinese Journal of Aeronautics 20 402—407 Zio, E. etal. 2003. The analytic hierarchy process as a systematic approach to the identification of important parameters for the reliability assessment of passive systems. Nuclear Engineering and Design 226 311 336... 

Chan P, Abhary K (1996) Design and evaluation of automated cellular manufacturing systems with simulation modeling and AHP approach a case study. Integr Manuf Syst 7(6) 39-52 Ho W (2008) Integrated analytic hierarchy process and its applications - a literatiue review. Eiu J... 

Bouyssou, D. et al. / EVALUATION AND DECISION MODELS A Critical Perspective Hanne, T. / INTELUGENT STRATEGIES FOR META MULTIPLE CRITERIA DECISION MAKING Saaty, T. Vargas, L. / MODELS, METHODS, CONCEPTS and APPUCATIONS OF THE ANALYTIC HIERARCHY PROCESS... 

Chan, F. T. S. 2003. Interactive selection model for supplier selection process An analytical hierarchy process approach. International Journal of Production Research. 41 3549-3579. 

In this chapter, principle introductions are conducted in terms of seismic response control, the analytic hierarchy process (AHP) and first-order optimization method. Through the parameters sensitivity analyses of 3-dimensional model for the Runyang Suspension Bridge (RSB), damper optimization for seismic control of the RSB under certain seismic input are realized, on the basis of the combination of the AHP and first-order optimization method. 

Among the several existing MCDM techniques, the Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) are the most widely used in solving decision-making problems. In AHP technique, the problem is modeled in a hierarchical structure showing the relationships between various components, namely, goal, criteria (and any subcriteria) and alternatives [16]. So, the components of decision problem are connected top-to-bottom in a way that the upper level node does not depend on the lower levels, and the elements presented in a node are independent of each other. This one-sided network fails to capture the complex interactions and feedbacks which might be present in the system To overcome this limitation, the ANP technique ras introduced by Saaty in 1996 (Saaty 1994). 

An, M., Huang, S. and Baker, C. (2007). Railway risk assessment-the fuzzy reasoning approach and fuzzy analytic hierarchy process approaches A case study of shunting at Waterloo depot. In Proceedings of the Institution of Mechanical Engineers, Part F Journal of Rail and Rapid Transit, 221(3), pp. 365-383. Bichou, K. (2008). Security and risk-based models in shipping and ports review and critical analysis. OECD/ITF Joint Transport Research Centre Discussion Paper. 

Based on the concept mentioned above, the objective of this research was, on one hand, to study the assessment model of microwave hot air systems using life cycle assessment, on the other hand, to characterize and analyze the green degree of assessment model using analytic hierarchy process and fuzzy decision-making method. 

In this study, the life cycle assessment of microwave hot air systems were developed using the analytic hierarchy process and the fuzzy comprehensive evaluation. The hierarchical structure consists of assessment aspect and assessment objective were established. The fuzzy assessment matrices of the assessment mathematical model were calculated using eigenvalue method and Gauss-Seidel iterative matrix. The life cycle assessment results show that the microwave hot air systems have a good green degree. 

For the critical items in Quadrant 3, we present a three-step method for global supplier selection. In the first step, we present a GP model for country selection this step shortlists a country using various qualitative and quantitative criteria. In the second step, we assess the risks of supply using the analytic hierarchy process (AHP). In the final step, we develop a multi-objective model with price and risk as the two conflicting objectives. For every product, we assign three different suppliers—a global supplier, a domestic primary supplier, and a domestic secondary supplier. Order allocation among the suppliers is optimally decided by the model. 

Preemptive GP ranks the objective fimctions with respect to the ordered preferences of the DMs and minimizes the deviations from the target values associated with each objective in the ranked order. Several different techniques can be used to derive preemptive priorities. One convenient way is to use discrete alternative multi-criteria decision-making methods such as rating, Borda count, pairwise comparison, or the analytic hierarchy process (AHP) method (see Ravindran et al. [2010] for an application). These methods also provide a numerical strength-of-preference value that can be used in non-preemptive GP models. The preemptive GP model formulation, assuming that the preference ordering of the objectives is Zy Zy Zy Zy as follows ... 

The analytic hierarchy process (AHP) and the the displaced ideal model (DIM) are systems analysis and multi-attribute methodologies (developed respectively by Saaty [6] and Zeieny [12]) which are well suited for a problem such as the evaluation of new manufacturing technologies. Both methodologies can be combined together in an overall evaluation process [13]. 

ABSTRACT By analyzing the hierarchy of safety factors in purification plant of natural gas, they are divided into personnel, equipment, environment and management. After the study of safety index, evaluation methods and fuzzy arithmetic method for each hierarchy, its fuzzy evaluation flow is given. During the evaluation, the weight of the factors and each hierarchy is decided by analytical hierarchical process, and the operational criterion adapts maximum membership degree. And this model is exemplified in purification plant of natural gas. The results show that the second fuzzy evaluation is effective to assess purification plant of natural gas. 

In this study, an analytic hierarchy structure was employed for evaluating product process and analyzing the process results. The effects of tangible aspects and objectives on the evaluation goal were systematically investigated using the second levels of tlie life cycle assessment model. The hierarchical structure of life cycle assessment of microwave hot air systems was shown m Figure 1. 

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