Multiple Criteria Decision-making Tool Research Articles

Urban resilience assessment: A multicriteria approach for identifying urban flood-exposed risky districts using multiple-criteria decision-making tools (MCDM)

As cities are vulnerable to diverse climate threats, operationalizing cities efficiently by addressing flood risk becomes an irreversible step. So, our research developed a multicriteria paradigm for identifying " where are flooding-exposed risky districts that should be prioritized for intervention?” based on two powerful indicators: flood vulnerability and flood exposure. Our methodology was tested in Alexandria, Egypt, which experiences the harshest rainfall annually and variations in socioeconomic and urban patterns like most global cities. One hundred thirteen climate-related Egyptian experts evaluated 44 flood risk-related indicators; the indicators were ranked using fuzzy AHP, followed by the differentiation of regions using TOPSIS, VIKOR, and WSM methods. Finally, map risky districts using interrelated horizontal layers of indicators. Our findings indicate that the spatial distribution of flood-prone districts increased in proximity to the traditional patterns of the city center and decreased when moving towards the dispersed patterns of the city's outskirts, indicating that urban form is a more effective indicator and has dual aspect effects (increase and decrease) in flood reduction when combined with other non-spatial indicators. Finally, a validation study was conducted to define the spatial congruency or mismatch between the simulated and realistic conditions. So, based on runoff data from 2015 to 2021, a deterministic coefficient (RC) and Nash-Sutcliffe efficiency (NSE) index were calculated with values of 0.89 and 0.93, respectively, indicating our analysis performed well. Our approach may assist policymakers in overcoming the shortage of data for contingency planning, especially in developing countries.

JMcDM: A Julia package for multiple-criteria decision-making tools

JMcDM: A Julia package for multiple-criteria decision-making tools

Experimental investigation and fuzzy TOPSIS optimisation of Ti6Al4V finish milling

ABSTRACT Ti6A14V is a well-known ‘Difficult to Cut’ material in the aerospace industry. Ti6Al4V shows strain hardening, poor thermal conductivity and chemical reactivity at elevated temperatures, which implies low machinability. This work presents an experimental investigation of 3D finish milling of Ti6Al4V material by Taguchi design of experiments, having L25 array. The considered process parameters are cutting speed, feed, depth of cut, tool type, coolant type and computer aided manufacturing strategy. The experimentation is conducted on the 3D finish milling process, and the performance in terms of tool life, tool wear and surface integrity were recorded. The fuzzy technique for order of preference by similarity to ideal solution, a multiple-criteria decision-making tool, was applied on experimental responses. The yielded optimum results are derived at minimum cutting speed, moderate depth of cut, feed rate per tooth and collaboration under high concentrated wet lubrication using a PVD-TiAlN cutting tool driven by streamline computer aided manufacturing strategy. In addition, analysis of variance confirms the influential process parameter contribution on the respective performance. Finally, optimised process parameters were applied for the gear bracket finish milling through streamline CAM strategy, which results in minimum flank and crater wear with an average surface roughness of 0.17 microns.

Application of Hexagonal Fuzzy MCDM Methodology for Site Selection of Electric Vehicle Charging Station

In this paper, the application of hexagonal fuzzy multiple-criteria decision-making (MCDM) methodology for the site selection of electric vehicle charging stations is considered. In this regard, four factors and thirteen sub-factors have been taken into consideration for E-vehicle charging site selection. In this research, the geographic information system (GIS) has been incorporated with MCDM techniques. The fuzzy analytic hierarchy process (FAHP) is used to obtain a fuzzy weight of factors and sub-factors. MCDM tools fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) and fuzzy complex proportional assessment (FCOPRAS) have been used to rank the selected sites. A centroid-based method for defuzzification and distance measure between two hexagonal fuzzy numbers (HFN) has been developed for this paper. A practical example in Howrah, India, is considered to show the applicability and usefulness of the model. The results depict the suitability of the proposed research. Comparative and sensitivity analyses have been demonstrated to check the reliability, robustness and effectiveness of the proposed method.

Multi-scenario and multi-criteria approach to evaluate prediction techniques used to recognise failure patterns

Predicting the next failure of a specific component in a machine results in higher performance of the equipment in terms of its reliability. This study examines the five most applicable prediction methods used to predict HVAC filter blockage. Considering different scenarios that use design of experiment (DOE), a multiple criteria decision making (MCDM) tool, known as TOPSIS, is utilised to compare the performance of each predictive technique according to their performance in various contexts. The results show that the performance of the system is improved when the best predictive method has been selected not only on the premises of a purely mathematical approach, but also when the solid mathematical prediction is supplemented by the judgments of experts and edited data. In addition, the empirical data is retrieved and a new method to evaluate the prediction techniques based on the applications of DOE and MCDM tools is illustrated.

Sustainable wastewater treatment plants design through multiobjective optimization

Nowadays, an adequate design of wastewater treatment plants taking into consideration all sustainability dimensions– economic, environmental and social- is fundamental. This can be achieved by implementing systematic methodologies where conceptual and mathematical tools can be used together. This contribution proposes a framework that uses total cost, consumed energy, and reclaimed wastewater as sustainability metrics. A mixed-integer nonlinear programming problem arises from a general superstructure for wastewater treatment plants. A case study from Mexico City is solved by a hybrid multiobjective optimization approach that combines lexicographic and ε-constraint methods. Solutions are provided in the form of a Pareto front. A modified technique for order of preference by similarity to ideal solution (M-TOPSIS) analysis is used as a multiple criteria decision-making tool to find the best trade-off solution. The optimal sustainable configuration resulted consists of three levels of treatment and 100% of treated water reuse.

Security perception of e-banking users in India: an analytical hierarchy process

When choosing online financial transactions, security is a paramount concern of users. Three categories of banks in India, namely public, private and foreign banks, have a completely different focus on technology and capabilities. The study aims at investigating e-banking users’ perception with regard to online risk for public, private and foreign banks. Online risk perception for the abovementioned banks was assessed on three major risk parameters, i.e. security aspect, privacy aspect, and trust; using a multiple-criteria decision-making tool, called the Analytical Hierarchy Process (AHP). The outcomes indicate that security risk is paramount among various aspects of perceived risk, followed by privacy and trust concern. Moreover, public sector banks are perceived to be the safest in this aspect. Public sector banks are also considered to be benign in terms of privacy and trust. Given the general user’s perception of risk generated by all the three risk parameters taken together, public sector banks are perceived to be the most secure, followed by private and foreign banks. The findings of this study have various implications for both research and practice. Private and foreign banks in India may adopt appropriate marketing strategies to achieve a favorable perception. Various studies have been conducted earlier on these factors and their interrelationship, but limited research has been carried out to demonstrate the importance of each of these factors in relation to the other as perceived by the user. Moreover, the study quantifies factors in order of their importance.

IMPROVING USERS SATISFACTION BY IMPLEMENTING THE ANALYTIC HIERARCHY PROCESS IN THE PUBLIC TRANSPORTATION SYSTEM

This paper develops investigations in the field of analytic hierarchy techniques that could be applied in public transportation systems. The study focuses particularly on the public transport bus services in Bucharest, the capital of Romania. The research aims to investigate the methodological feasibility of the analytic hierarchy process to analyze and measure the perceptions and needs of the Romanian public transportation users. Towards this objective, the study presents the current state of the Bucharest bus network. Furthermore, an investigation is conducted based on one of the most used multiple criteria decision-making tool -Analytic Hierarchy Process (AHP). Unlike most of the previous studies, this analysis has a double approach: researching the essential total quality management principles in public transportation and simultaneously developing a one stage methodology used for measuring the quality of the Romanian public transportation system. This final step involves using the AHP methodology to determine the priority of service quality attributes. Our contribution to the literature focuses on the advantage of using an analytic hierarchy technique in evaluating complex decisions in terms of public transportation. This contribution provides an initial analysis of the public transportation field in the Capital of Romania. Additionally, the study develops the premises for our further research and concludes on the efficiency and sustainability of an AHP method assessment in the local transportation network.

An integrated approach for sustainability assessment with hybrid AHP-LCA-PI techniques for chitosan-based TiO2 nanotubes production

Designing a sustainable process requires the aid of systematic multivariate assessment method that considers the dimensions of economic, social and environmental impact. This work presents a sustainability assessment framework for the commercial production of chitosan-based titanium dioxide (TiO2) nanotubes using a hybrid method consisting of analytical hierarchy process (AHP), life cycle assessment (LCA) and process integration (PI) techniques. Despite the attractive financial return of the case study as mentioned, its adverse environmental impacts pose challenges to commercialisation due to large consumption of chemicals and waste discharge. Hence, five production alternatives with resource conservation options were evaluated. AHP was adopted as a multiple criteria decision-making tool considering all three dimensions of sustainability; the latter include capital and operating costs, handling risk, alongside with environmental criteria, namely cumulative energy demand (CED), global warming potential (GWP) and water depletion (WD). The selected alternatives were validated through experiment works. Reutilisation of calcium chloride was determined to be the preferred configuration as it fulfilled all three sustainability dimensions, as compared to other alternatives.

A geospatial approach to flash flood hazard mapping in the city of Warangal, Telangana, India

Abstract Dense urbanization leading to uncontrolled transformations within settlements result in flash flooding with overflowing drains leading to a greater inconvenience for the public and damage to private properties. Hence mapping of flash floods would be useful in identifying the high-risk flood zones for disaster response and urban services, during emergencies with rainfall events of high intensity. This article aims to prepare a flood hazard map of Warangal Municipal Corporation (WMC) in Telangana State, India. WMC is chronically affected due to a rise in water levels resulting in flash floods, with an increase in encroachments. The factors considered in this study are rainfall (curve number), surface slope and surface roughness, type of soil, and distance to main channel, drainage density, and land use cover. To decide the relative weight of the impact of each flood causative factors an Analytical Hierarchical Process (AHP) was used. Accordingly, a composite Flood Hazard Index (FHI) has been derived by using the multiple-criteria decision-making tools by integrating these into a Geographical Information System (GIS). The Soil and Water Assessment Tool (SWAT) in Quantum GIS (QGIS), which is a hydrological model, was used to evaluate the projection of streamflow over the water basin and model parameters were optimized using water balance equations during calibration and validation periods.

Multiple-Criteria Decision-Making for Assessing the Enhanced Geothermal Systems

This paper presents the main features of a multiple-criteria decision-making tool for economic and environmental assessment of enhanced geothermal systems projects. The presented holistic approach takes into account important influencing factors such as technical specifications, geological characteristics, spatial data, energy and heat prices, and social and environmental impact. The multiple-criteria decision-making approach uses a weighted decision matrix for evaluating different enhanced geothermal systems alternatives based on a set of criterions which are defined and presented in this paper. The paper, defines and quantifies new criterions for assessing enhanced geothermal systems for a particular site. For evaluation of the relative importance of each criterion in decision making, the weight is associated with each of the listed criterions. The different scenarios of end-use applications are tested in the case study. Finally, in the case study, the data and statistics are collected from real geothermal plants. The case study provides results for several scenarios and the sensitivity analysis based on which the approach is validated. The proposed method is expected to be of great interest to investors and decision makers as it enables better risk mitigation.

A Decision Support Framework for Assessing the Contextual Factors for Complex Highway Projects

Traditional strategies for highway projects during the 1950s and 1960s focused on three dimensions of project management: cost, schedule, and technical (scope). Recently, with the focus shifting towards reconstruction/rehabilitation projects, project management strategies have shifted to include other project management dimensions. The Second Strategic Highway Research Program (SHRP2) project R-10 examined the best practices for managing complex renewal projects. The primary outcome of the study was a recommendation to utilize a five-dimensional project management planning (5DPM) model that added context and financing as two new dimensions to the traditional dimensions of cost, schedule, and technical. Pilot testing of the 5DPM implementation suggested that the most complicated dimension to assess during the project management planning phase for a complex project is the context dimension. Currently there is no efficient, structured process for evaluating the context dimension on complex projects within the 5DPM framework. Given this, the objective of this study is to develop a decision support framework which can be used by different transportation agencies when assessing contextual factors and assigning complexity rating scores. The framework uses a structured analytical process as opposed to the more subjective scoring used during the 5DPM workshops. As a major part of its methodology, this research uses a multiple-criteria decision-making tool called analytical hierarchy process in developing the framework. The paper presents two implementation examples which demonstrate the feasibility of the developed framework for a rebuild project and an expansion project.

Multiple-Criteria Decision-Making Tool for Local Governments to Evaluate the Global and Local Sustainability of Transportation Systems in Urban Areas: Case Study

AbstractEfficient management of urban transportation systems is a challenge for any local government that wishes to improve public wellbeing and comfort. With that end in mind, this paper proposes ...

Decision Support Framework for Transit-Oriented Development Projects

Although the use of personal automobiles in the United States continues to grow, there are increasing concerns about the possible effects of automobile-dependent transportation, including environmental concerns, the reduction in the quality of life caused by long commutes, and a decline of community and societal interactions. These concerns have led to discussions on the revitalization of public transportation systems. To counter the problem of congestion resulting from modern urbanization, urban planners have developed the idea of transit-oriented development (TOD), designed to encourage the use of public transit and the creation of pedestrian-friendly environments. The plethora of literature on this subject is no surprise, considering the issues of revitalization of community living and affordable housing and related factors directly influencing and getting influenced by TOD. Notwithstanding the abundance of literature on TOD, the literature review uncovered few studies that somewhat address the important question, “How can a transit agency choose between alternative TOD sites to develop or build?” Given this, the purpose of this research is to develop a decision support framework that can be used by different transit agencies when choosing a TOD site to develop or build by incorporating and assessing unique success factors and their weights. This research uses a multiple-criteria decision-making tool called the analytic hierarchy process in developing that framework. The paper presents two implementation examples that demonstrate the feasibility of the developed decision support framework for both a large, urban transit district and a smaller, more rural transit agency.

Decision-making through a fuzzy hybrid AI system for selection of a third-party operations and maintenance provider

With the outsourcing and the increasing demand of facilities management services, we observe the growing of multi-technical contracts in real estate operations and maintenance (O&M). Selection of one or more contractors is actually complex and important financial and quality of service challenges depend on it. The present paper proposes a multiple-criteria decision-making tool whose objective is to predict contractors' performances and to select the one who can best respond to O&M demands. In order to build the heuristic between technical, commercial and quality criteria and the expected performances, a neuro-fuzzy system (NFS) associated with a hybrid and adaptive genetic algorithms (GA) method has been developed. Important problems are considered: data pre-processing, problem of data scarcity to provide a sufficient number of data to the NFS and optimisation of hybridisation or adaptation parameters for GA. A case study, concerning the clients' satisfaction levels for O&M contractors as a final indicator for decision-making will prove the relevance of this approach.

A performance evaluation framework for technical institutions in one of the states of India

Purpose – Technical education plays an important role in the development of a country in this age of knowledge economy. Indian technical education system is facing many opportunities and challenges, one of which is how to assess the performance of technical institutions based on multiple criteria. The purpose of this paper is to describe and illustrate an application of a structured approach to determine relative efficiency and ranking of a set of private engineering colleges under multi-criteria environment. Design/methodology/approach – To cater to the increasing need of technical manpower, a very large number of private engineering colleges have been established in the state of West Bengal of eastern India within a very short period. Uniform and acceptable quality of the graduates from many of these private engineering colleges is a concern today and therefore the need for performance evaluation and ranking of these colleges is paramount. For the proposed framework a comparatively new multiple criteria decision-making tool, multiple objective optimization on the basis of simple ratio analysis (MOOSRA) is applied for performance evaluation of eight private engineering colleges taking into account some selected criteria. The subjective weights of the criteria are determined using fuzzy analytic hierarchy process (AHP). Findings – For the analysis, the required data have been provided by the management of the colleges for the academic year of 2011-2012. Based on request of the management identities of these institutes are not disclosed. The institutes are considered as anonymous institute and coded as A, B, C, D, E, F, G and H, respectively. The result of the study reveals that E is the best and the ranking the authors get is in the order of E > F > A > H > D > C > G > B. The result shows that composite performance scores of institutions A, E and F are above the mean performance score value. Therefore these three institutions can be considered as the benchmark or peer group for the remaining five institutions which lie below the mean line of the performance score value. Originality/value – This paper provides a comprehensive yet detailed methodology for performance evaluation of academic institutions. The novelty in the approach is that fuzzy AHP and MOOSRA are being used as a benchmarking technique in a simple methodology which is generic in nature. It is one of the few studies that evaluate the performance of technical institutions in India.

THE APPLICATION OF THE ANALYTIC HIERARCHY PROCESS FOR EVALUATING CREATIVE PRODUCTS IN SCIENCE CLASS AND ITS MODIFICATION FOR EDUCATIONAL EVALUATION

To design and to manufacture in science learning are increasingly important in science education. Yet, evaluation techniques in school for evaluating students’ creative products are apparently left behind. With the aim of developing an evaluation method to evaluate creative products in science and technology class, this study constructed a set of criteria with data collected from teachers and students. The analytic hierarchy process (AHP), a multiple criteria decision-making tool for single rater, was selected for the purpose of weighting and evaluating students’ products. However, the traditional AHP used one rater’s pair-wise comparisons; its subjectivity and complexity limit its applications in school. For solving this problem, this study developed an advanced technique, called direct-rating AHP (DR-AHP), to extend the applicability of the traditional AHP. The DR-AHP is used to obtain weights or preferences for criteria/alternatives by a process of directly ranking criteria/alternatives by single/multi rater(s), checking consistency, and developing a rank vector matrix. The DR-AHP was implemented in obtaining criteria weights of a hierarchy framework for creative products evaluation by a group of science educators (N = 13) and field-tested in ranking creative products by another group of science teachers (N = 9). Results showed its superiority in objectivity and efficiency over traditional ways of evaluation. The results also demonstrate how the AHP and DR-AHP are capable of helping evaluators systematically construct criteria and/or to evaluate students’ creative products for classroom instruction as well as during many other activities.

A study on the effects of inter-organizational factors on the supply chain performance

Article history: Received March 5, 2012 Received in Revised form March, 15, 2012 Accepted 20 May 2012 Available online May 28 2012 In the current competitive environment, managers do their best to convert organizations under their supervision into competitive and responsive through creating capability of timely delivery of quality products and services. In the other word, they try to create value for their customers, which yield more profitability for stakeholders. In line with this, determining of interorganizational factors and the relationships among these variables and supply chain performance plays an important role in achieving these objectives. The relationship modeling is a type of multiple criteria decision-making (MCDM) problem, which requires applying experts to determine the relationships. The Decision Making Trial and Evaluation Laboratory (DEMATEL) is an MCDM tool, which not only can convert the relationships among cause and effect criteria into a visual structural framework, but also it can be used as a technique to handle the inner dependences within a set of criteria. This paper proposes an effective solution based on DEMATEL approach to help managers evaluate the relationships between interorganizational factors and supply chain performance. © 2012 Growing Science Ltd. All rights reserved.

Suppliers ranking by cross-efficiency evaluation in the presence of volume discount offers

The performance of each supply chain is significantly related to the performance of the suppliers. Due to the multiple criteria nature of the supplier selection problem, data envelopment analysis (DEA), as a multiple criteria decision-making tool, seems to be an appropriate method. This paper specifically focuses on the supplier selection problem when the suppliers offer volume discounts to encourage the purchase of large volumes. However, in all the papers which deal with the volume discount concept in DEA models, each decision-making unit (DMU) is free to decide which outputs and inputs to emphasise that in turn cause to have many efficient DMUs. Therefore, the main purpose of this study is to use the cross-efficiency method when suppliers offer volume discounts. A numerical example demonstrates the application of the proposed method.

A data envelopment analysis model for selecting suppliers in the presence of both dual-role factors and non-discretionary inputs

Supplier selection is the strategy adopted by the manufacturer, to evaluate and select suppliers, which can fulfil the requirements of the manufacturer. To this end, data envelopment analysis (DEA), as a multiple criteria decision-making tool, has been applied for several times. However, conventional DEA models cannot simultaneously consider dual-role and non-discretionary factors. The objective of this paper is to propose a DEA model for ranking suppliers in the presence of both dual-role factors and non-discretionary inputs. A numerical example demonstrates the application of the proposed model.