A multi-level evaluation model for the recognition and assessment of impact factors associated with intercontinental power interconnection projects

Supporting Partnering Relation Management in the Implementation of Construction Projects Using AHP and Fuzzy AHP Methods

PT Vizta Pratama Bengkulu is a branch of a franchise company engaged in family karaoke entertainment services, founded by a well-known dangdut singer, Inul Daratista and starting its first operation in 2005 in Kelapa Gading area. PT. Vizta Pratama Bengkulu has not used the Decision Support System Application. The decision to determine the recipient of the annual bonus is only to calculate the total value based on 3 criteria, namely responsibility, discipline, honesty without using a decision support method, therefore sometimes it is felt that the giving of employee annual bonuses is not right on target. Decision support system for giving annual bonus at PT. Vizta pratama using the analytical hierarchy process (AHP) method is a desktop-based application that has implemented the AHP (Analytical Hierarchy Process) method, this application runs on a Windows operating system created using the Visual Basic .NET programming language and SQL Server 2008r2. This application can be used to assist in the assessment process in determining the annual bonus at PT. Vizta Pratama Bengkulu where this application uses 4 predetermined criteria and then processed using the AHP (Analytical Hierarchy Process) method so as to produce values that will be ranked. Based on the results of the Blackbox testing that has been carried out, it can be concluded that the decision support system for providing annual bonuses at PT. Viztapratama by using the analytical hierarchy process (AHP) method is able to run well and can overcome data input errors by users and the SPK application with the Analytical Hierarchy Process method has provided effective results in accordance with the results of calculations using paired comparisons of 4 criteria where the comparison of pairs of criteria must produce consistent weighting criteria.

Groundwater resources are essential for drinking water, irrigation, and the economy mainly in semiarid environments where rainfall is limited. Currently, unpredictable rainfall due to climate change and pollution on the Earth’s surface directly affects groundwater resources. In this area, most people depend on groundwater resources for irrigation and drinking purposes, and every summer, most of the area depends on groundwater in a semiarid environment. Hence, we selected two popular methods, the analytical hierarchy process (AHP) and multiple influence factor (MIF) methods, which can be applied to map groundwater potential zones. Nine thematic layers, such as land use and land cover (LULC), geomorphology, soil, drainage density, slope, lineament density, elevation, groundwater level, and geology maps, were selected for this study using remote sensing and geographic information system (GIS) techniques. These layers are integrated in ArcGIS 10.5 software with the help of the AHP and MIF methods. The map of the groundwater potential zones in the study area revealed four classes, i.e., poor, moderate, good, and very good, based on the AHP and MF methods. The groundwater potential zone area is 241.50 (ha) Poor, 285.64 (ha) moderate, 408.31 (ha) good, and 92.75 (ha) very good using the AHP method. Similarly, the MIF method revealed that the groundwater potential classes were divided into four classes: 351.29 (ha) poor, 511.18 (ha), moderate, 123.95 (ha) good, and 41.78 (ha) very good. The results were compared to determine which methods are best for planning water and land resource development in specific areas that have basaltic rock and drought conditions. Both groundwater potential zone maps were validated with water yield data. The receiver operating characteristic (ROC) curve and area under the curve (AUC) model results are found to be 0.80 (good) and 0.93 (excellent) using the MIF and AHP methods, respectively; hence, the AHP method is best for delineation of groundwater potential zone maps and groundwater resource planning. The present study’s framework and the results will be valuable for improving the efficiency of irrigation, conserving rainwater and maintaining the ecosystem in India.

In order to solve the problem that the current index system of distribution network reliability for power consumer (DNRPC) is not yet perfect, the index system is expanded in this paper, and a comprehensive evaluation method of DNRPC based on analytic hierarchy process (AHP) and entropy combination method is put forward. Firstly, the concept and connotation of DNRPC are expanded. Secondly, three new evaluation indexes are proposed to expand the existing index system. Thirdly, AHP method and entropy method are used to determine the subjective and objective weight of the reliability indexes. The least squares method is used to optimize the index weight and obtain the comprehensive evaluation result. Finally, a concrete example is given to demonstrate the validity and feasibility of the proposed index system and the comprehensive evaluation method.

This research is dedicated to the modelling of decision process occurring during the implementation of construction projects. Recent studies generally do not assess the robustness of the decisions regarding the possible changes during the construction project implementation. However, such an assessment might increase the reliability of the decision-making process. We addressed this gap through a new model that combines the decision-making process modelling with the AHP method and includes the analysis of model stability concerning stakeholders’ behaviour. We used the Analytic Hierarchy Process (AHP) and Decision tree methods to model the decision-making process. The proposed model was validated on a case study of multiple construction projects. The assessment was performed from individual investor’s and independent expert’s perspectives. The criteria for the assessment were selected according to the principles of sustainability. We performed the sensitivity analysis, making it possible to assess the possible changes of the decisions depending on the potential patterns of the decision-makers’ behaviour. The results of the study show that, sometimes, small fluctuations in the project factors affect the project selection indicating the possible lack of the robustness of the project decisions.

Comprehensive performance evaluation is a fundamental part of the design and operation optimization of distributed integrated energy systems (IES), and the evaluation is currently focused on three types of elements: economic, energy efficiency and environmental protection. In this paper, energy use quality elements are proposed from the high energy supply requirements of users for distributed IES and characterized by the supply-demand imbalance rate indicator. Then the Analytic Hierarchy Process (AHP) and the information entropy method are combined to form a combined evaluation method by weighing the subjective and objective methods. The comprehensive performance evaluation of distributed IES with nine indicators considering four elements of economy, energy efficiency, environmental protection and energy use quality is realized. The feasibility and validity of the proposed indicators and the difference between the proposed combination method and the existing combination method are verified by the calculation examples. In the single-objective optimization with optimal energy use quality, the supply-demand imbalance rates for heat and cold are −0.05 and −0.035, respectively, which are the best among the five optimization schemes and fully guarantee the stability and quality of energy supply. However, its CO2 emission of 5738.91 (t/year) shows that this indicator is not suitable for the limitation of single-objective optimization, and it would be more suitable for comprehensive optimization with the above three indicators. The weights of operation cost, heat and cold supply-demand imbalance in the AHP method are 0.2247,0.0539,0.0539. The corresponding weights in the information entropy method are 0.0930,0.1670,0.1864. The corrected values are 0.1999, 0.0861, 0.0961. The results show the corrective effect of the information entropy method on the AHP. In addition, the combination method proposed in this paper corrects the configuration cost term to 0.2032, which is larger than both 0.1588 in the AHP method and 0.1388 in the information entropy method, highlighting the difference from existing combination methods. The above data show that the comprehensive evaluation by the AHP-information entropy method can effectively consider the four elements’ role. It provides a new idea for the research on the impact of distributed IES energy storage on the energy use quality of the system and the construction and operation optimization of the comprehensive performance evaluation indicator of the system.

Bureau of Student Advisory Center (BSAC) Universitas Pembangunan Panca Budi is a center for career development and character building for students. In this case, a soft skill seminar is conducted to find the best candidate employees in the field of recruitment offered based on the criteria of student soft skill training. Determining the level of soft skill competences of students using the Analytical Hierarchy Process (AHP) method and the Preference Ranking Organization Method for Enrichment Evaluation (PROMETHEE). For decision support systems using the AHP and PROMETHEE methods in determining the level of soft skill competencies, in order to obtain prospective employees who have the required soft skill competency level. Data collection was carried out by conducting research. The data is taken from the seminar results with 100 participants. The data that has been collected, processed and analyzed before being used as input and output as a basis for learning or training using the AHP and Promethee methods. Based on the calculations of the two methods, namely the AHP and Promethee methods, there are differences in calculations. In other words, because Promethee does not support the determination of weights and the hierarchy of criteria and does not have the assurance of consistency when determining weights like AHP. So that the program execution has a different time in the results, in the AHP method, program execution until the final result is obtained is better than the Promethee method. AHP has advantages in determining weights and criteria hierarchy, while Promethee has advantages in the alternative ranking process using different preference and weight functions.

The relative importance of each pollution factor in analytical hierarchy process (AHP) method comes from pooling expert opinions in general. Because expert opinions are based on information and judgment criteria, determining their weight may lead to uncertainty.. Therefore, an improved AHP method had been developed. The process of the improved AHP method involved four key procedures. The weights of pollution factors were completely related to the objective monitoring data through the standardization of these procedures. The environmental comprehensive quality of water and sediment of Xuanwu Lake, Nanjing, China had been evaluated. The environmental quality comprehensive indices (EQCI) of the water in 1991-1995 and 1996-2000 were 3.32 and 1.85, respectively, indicating that the water quality improved. The EQCI of the sediment in 1995 and 2000 indicates that the sediment contamination decreased from 1995 to 2000. Such results agreed with the fact that the lake had been under comprehensive control. However, with the classical AHP method, the EQCI of the sediment in the northwestern part of the lake may have indicated that sediment contamination increased from 1995 to 2000. The discrepancy may have resulted from the judgment difference of the experts. The improved AHP method can avoid arbitrariness of subjective judgment and can reflect the real influential factors of environment pollution in different periods or regions.

With the rapid development of science and technology, new technology is starting to be used in various fields including education. Education has a very important progress in a nation, because it can optimize individual potential. The educational process in higher education has a big influence on a student's future. However, there are many students who experience difficulties in choosing a college major after graduating from vocational high school (SMK) or senior high school (SMA), because of the complexity in identifying the suitability between interests and study programs. Decision making is a problem that everyone faces, especially in choosing an appropriate college major. There are many factors to consider, and with many options available, the decision-making process can be difficult. To overcome this problem, this research aims to create a decision support system (DSS) using the AHP (Analytical Hierarchy Process) and TOPSIS (Technique For Order By Similarity To Ideal Solution) methods. The AHP method is used to solve complex problems by structuring a hierarchy of criteria and developing weights or priorities. However, when the AHP method is used with many criteria and alternatives, other methods are needed for more effective results. Therefore, a combined method of AHP and TOPSIS was chosen, where AHP focuses on pairwise comparison matrices and consistency analysis, while TOPSIS can measure relative performance and alternative decision making simply and efficiently. The results of research on decision support systems for selecting majors using the AHP and TOPSIS methods show that the application of the combined AHP-TOPSIS method can be used to determine the best alternative in selecting majors by comparing alternatives based on predetermined criteria. In addition, system testing results show that the system functions as expected and meets user needs. With a decision support system for selecting college majors implemented on the website, it can simplify the decision-making process for students and BK teachers in choosing college majors. The results of the calculation of the percentage of system feasibility in blackbox testing show a value of 95.71%, which indicates that this major selection decision support system website can be used.

Multi-attribute Decision Model of Green Supplier Selection under the Low-carbon Economy

Supplier selection is one of the most important things in the company's purchasing activities. The selection of suppliers must be done carefully; if done wrong, it can cause disruption to the company's operations. Supplier selection becomes a multi-criteria problem, which includes qualitative and quantitative factors. One method that can be used for supplier selection is the AHP (Analytical Hierarchy Process) method. This research was conducted at a footwear industrial company, PT. Adis Dimension Footwear. The problems found in this research are: Which chemical supplier will be chosen by PT Adis Dimension Footwear based on the AHP method? Then what is the order of priority criteria and sub-criteria in the selection of chemical suppliers at PT. Adis Dimension Footwear? The sample for this research is the decision-makers and the parties who are in the purchasing and warehouse departments and know the performance of suppliers. This study uses the AHP (Analytical Hierarchy Process) method. From the results of the research, the importance of the criteria in supplier selection produces the following weights: The first order is quality criteria with a weighted value of 0.6333. Furthermore, the second rank is the criteria for delivery time with a weight of 0.2605, and the third is the price criteria with a weight of 0.1062. The chemical supplier selected based on research using the AHP method is Grand Chemical, which has a total weight of 0.4285. Asia Chemical Supplier comes in second with a total weight of 0.4093. Binzhou Longfeng Chemical Supplier comes in third place with an overall score. Keywords: Supplier selection, Analytical Hierarchy Process (AHP), footwear industrial, chemical supplier.

Optimal study of the rural house space heating systems employing the AHP and FCE methods

A review of tender evaluation practices from around the world revealed the inadequacy of the ‘lowest bidder’ criterion for contractor selection. In response to this inadequacy, many countries have introduced qualifications to this cri terion and established procedures for the evaluation process. The objective of the qualifications is to select a suitable contractor whilst fostering compet itiveness. Using a multi criteria decision making (MCDM) approach, the study identified eight contractor attributes from the literature, which are thought to be indicators of contractors’ capability to execute a contract and meet certain project specific criteria. Employing a case study project, the tenders of eight contractors short listed for the project were evaluated with the attributes using the “lowest bid”, multi attribute analysis (MAA) and analytic hierarchy process (AHP) methods. The results showed that the two multi criteria decision making methods indicated the selection of contractors other than what the ‘lowest bidder’ criterion indicated. Comparing the results of the MAA and AHP meth ods, it is evident that the two methods differed very little in their ranking of the contractors. This implies that the more complex nature of AHP and the extra efforts it requires have only a minor influence on the final ranking of contrac tors and seems to suggest that the extra cost of using AHP is not justified.

Application and validation of AHP and FR methods for landslide susceptibility mapping around choke mountain, northwestern ethiopia

Scenario‐based test methods are employed to assess the safety and performance of autonomous vehicles. The analytic hierarchy process (AHP) method is a common assessment method for determining the criticality of test scenarios. However, the AHP method is subjective and less reproducible when performed by different persons, as the elements of pairwise comparison values that are directly linked to the outcome must be assigned by the person involved. This paper proposes a novel AHP method that automatically generates pairwise comparison values by optimizing the correlation between performance metrics and risk of test scenarios by simulation. Performance metrics are defined as the minimum relative distances and corresponding relative velocities between vehicles, and the risk of the test scenario is determined by the pairwise comparison values of AHP. The novel AHP method was evaluated using a cut‐in scenario. The results showed that the minimum relative distance and the risk determined by the novel AHP method achieved a better correlation coefficient of −0.96, which is better than the conventional AHP of −0.828 and Fuzzy AHP of −0.824. These results suggest that the criticality of the test scenarios determined by the novel AHP method can more accurately reflect real‐world driving environments.