Multi-criteria Decision-making Applications Research Articles

Novel picture fuzzy power partitioned Hamy mean operators with Dempster-Shafer theory and their applications in MCDM

In some multi-criteria decision-making (MCDM) scenarios, decision makers must address challenges like handling uncertain and incomplete information, managing biases in criteria values, and assessing interrelationships among criteria based on their partitioning as per their characteristics. To tackle these challenges, a picture fuzzy set (PFS) can be utilized to quantify vague information, Hamy mean (HM) can be used to consider criteria interrelationships while the power average (PA) mitigates any kind of biasness. Also, to overcome the limitations of persistence and invariantess in algebraic operations, Dempster-Shafer theory (DST) is employed. By integrating the conventional HM with the traditional PA under partitioning, this paper first introduced the novel power partitioned Hamy mean (PPtHMq\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$PPtHM^q$$\\end{document}) operator. Then, this operator is extended for picture fuzzy numbers (PFNs) with DST and two novel operators are introduced, which are named as picture fuzzy power partitioned Hamy mean (PFPPtHMDSTq)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(PFPPtHM^q_{DST})$$\\end{document} and picture fuzzy weighted power partitioned Hamy mean (PFWPPtHMDSTq)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(PFWPPtHM^q_{DST})$$\\end{document} with some desirable properties. Moreover, based on these operators, a new method for MCDM in the PFS environment has been designed. The paper illustrates their application in selecting the best hotel among four alternatives (B1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$B_1$$\\end{document}, B2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$B_2$$\\end{document}, B3\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$B_3$$\\end{document}, B4\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$B_4$$\\end{document}) based on five criteria, which are partitioned into two sets. Results indicate that the best and worst alternatives under these operators are hotels B1\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$B_1$$\\end{document} and B4\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$B_4$$\\end{document}, respectively. Sensitivity analysis explores the impact of granularity parameter variations, and comparative analysis demonstrates the effectiveness of the presented operators. Overall, the study concludes that these operators offer flexibility, generality, and consistency for analyzing MCDM problems in PFS environments.

Determining the most appropriate stormwater management strategies within the development of urban landscape infrastructure using the TOPSIS method: applications to Rize city

ABSTRACT In this study, the application of multi-criteria decision-making (MCDM) methods in determining the most appropriate stormwater management strategy is examined using different areas in Rize. The determination of the most appropriate stormwater management practices for the Rize coastal park and Güneysu-Rize connection highway with TOPSIS is presented in detail within this study. In this context, commonly used applications suitable for urban areas are discussed. The criteria and their weights used for the evaluation of the selected applications were determined by consulting expert opinions from leading researchers. The most suitable applications in different scenarios such as changes in the cost or the amount of precipitation for Rize coastal park and Güneysu-Rize connection road were determined by the TOPSIS method. The TOPSIS analyses’ ranking of the ideal solutions matches the results of the SWMM simulations one to one. SWMM results confirm that the outcomes of TOPSIS are the alternatives that provide maximum decrease in surface runoff.

Assessment of Third-Party Reverse Logistics Provider Through the SWARA-WASPAS Integrated Framework

The selection of the most suitable third-party provider for reverse logistics (RL) activities is a key factor in initiating effective RL processes. However, the process of identifying the optimal third-party provider involves navigating through various conflicting objectives and criteria. This task is intricate and time-consuming, necessitating the application of multi-criteria decision-making (MCDM) approaches. This study addresses the evaluation and selection of the best 3PRLP by introducing a comprehensive MCDM framework. Therefore, this study aims to assist a manufacturer specializing in milk and dairy products who has opted to transfer its reverse logistics operations to a logistics service provider. The objective is to aid them in selecting the most suitable 3PRLP. The proposed framework incorporates the SWARA (Step-wise Weight Assessment Ratio Analysis) technique for determining weights and the WASPAS (Weighted Aggregated Sum Product Assessment) method for thoroughly evaluating alternatives. In this study, a panel of four experts made a joint decision after identifying six criteria and five alternatives. The research concluded that the reverse logistics cost (C1) emerges as the most pivotal factor, with the service quality of reverse logistics (C3) being recognized as the least significant criterion. As a result, A1 stands out as the top choice among the 3PRLP.

Application of multi-criteria decision-making on low-impact development practice selection for the Kinyerezi River sub-catchments in Dar es Salaam, Tanzania.

The impermeable areas in catchments are proportional to peak flows that result in floods in river reaches where the flow-carrying capacity is inadequate. The high rate of urbanization witnessed in the Kinyerezi River catchment in Dar es Salaam city has been noted to contribute to floods and siltation in the Msimbazi River. The Low-Impact Development (LID) practices that includes bio-retention (BR) ponds, rain barrels (RBs), green roofs (GRs), etc. can be utilized to mitigate portion of the surface runoff. This study aims to propose suitable LID practices and their sizes for mitigating runoff floods in the Kinyerezi River catchment using the Multi-Criteria Decision-Making (MCDM) approach. The results indicated that the BR and RBs were ranked high in capturing the surface runoff while the sediment control fences were observed to be the best in reducing sediments flowing into the BR. The proposed BR ponds were greater than 800 m2 with 1.2 m depth while RB sizes for Kinyerezi and Kisungu secondary schools and Kinyerezi and Kifuru primary schools were 2,730; 2,748; 1,385; and 1,020 m3, respectively. The BR ponds and RBs are capable of promoting water-demanding economic activities such as horticulture, gardening, car washing while reducing the school expenses and runoff generation.

Interval-valued T-spherical fuzzy extended power aggregation operators and their application in multi-criteria decision-making

Abstract As an effective tool to show the fuzziness of qualitative information, the interval-valued T-spherical fuzzy set can utilize three kinds of information, namely, membership, abstinence, and non-membership, to show the opinions of decision-maker. Given this advantage, many interval-valued T-spherical fuzzy multi-criteria decision-making (IVTSF-MCDM) methods have been designed. However, most of the existing IVTSF-MCDM methods have a common limitation that the inability to effectively show the impacts of extreme data. To address this limitation, this study develops a novel MCDM method based on interval-valued T-spherical fuzzy extended power aggregation operator. First, interval-valued T-spherical fuzzy cross-entropy (CE) and interval-valued T-spherical fuzzy symmetrical CE are defined to measure the difference between two interval-valued T-spherical fuzzy numbers, which are used to determine criteria weights in MCDM. Second, interval-valued T-spherical fuzzy extended power average operator and interval-valued T-spherical fuzzy extended power geometric operator are proposed, and their properties are investigated. Moreover, in view of that criteria may be assigned to different weights, this study defines interval-valued T-spherical fuzzy extended power weighted average operator and interval-valued T-spherical fuzzy extended power weighted geometric operator to derive the order of alternatives. Finally, the applicability of the proposed method is validated by the case about investment country selection, while the sensitivity and comparison analyses are also conducted to further prove its advantages and effectiveness.

Linguistic q-rung orthopair fuzzy Z-number and its application in multi-criteria decision-making

This paper proposes a new linguistic model called Linguistic q-Rung Orthopair fuzzy Z-number (LqROFZN), which combines the advantages of linguistic variables, Z-number and q-Rung Orthopair Fuzzy numbers. It can be used as a powerful tool for uncertain decision-making, which can effectively improve the accuracy and reliability of the decision-making results, and has a notable application prospect for the fields of information decision-making, risk assessment, diagnosis and so on. In this paper, firstly, the definition of LqROFZN and its operational rules are given, a new distance measure and the concept of entropy are given under LqROFZN, and the entropy of LqROFZN can assess the credibility situation of LqROFZN. Next, two aggregation operators under LqROFZN are given, namely the Linguistic q-Rung Orthopair fuzzy Z-number weighted aggregation (LqROFZWA) operator and the Linguistic q-Rung Orthopair fuzzy Z-number weighted Geometric aggregation (LqROFZWGA) operator. Finally, the MCDM method under LqROFZN is given and the credibility of the evaluation results is assessed using the entropy of LqROFZN. In a set of actual airline aircraft selection cases, the feasibility and advantages of the proposed method are verified through comparative analysis with other methods.

Application of Multi-Criteria Decision-Making (MCDM) to Select the Most Sustainable Power-Generating Technology

In response to the growing importance of sustainability and regulatory pressures, companies are increasingly engaging in sustainable projects to mitigate environmental and social harm. Therefore, it is crucial to incorporate sustainability considerations during selecting construction projects in the feasibility phase. This study aims to identify a comprehensive set of sustainability criteria and sub-criteria to help the owners of power-generating plants to select the most sustainable technology for their new projects. Sixteen criteria are identified and categorized under the pillars of sustainability: economic, social, and environmental, plus the technical category. To illustrate practical application, a case study demonstrates the use of these essential sustainability criteria through a hybrid multi-criteria decision-making (MCDM) model for power-generating technology ranking. The results suggest that when stakeholders’ perspectives are weighted approximately equally, considering all sustainability pillars, natural gas with carbon capture is favored for sustainability. A three-scenario sensitivity analysis was performed involving expert opinions from one of the largest power-generating companies in Canada. This integrated generic model can be utilized by industry experts to apply multi-dimensional rational decision-making techniques to solve the complex problem of selecting the most sustainable alternative in construction projects.

Bloodmobile location selection for resilient blood supply chain: a novel spherical fuzzy AHP-integrated spherical fuzzy COPRAS methodology

PurposeBlood availability is critical for saving lives in various healthcare services. Ensuring blood availability can only be achieved through efficient management of the blood supply chain (BSC). A key component of the BSC is bloodmobiles, which are responsible for a significant portion of blood donation collections. The most crucial factor affecting the efficacy of bloodmobiles is their location selection. Therefore, detailed decision analyses are essential for the location selection of bloodmobiles. This study proposes a comprehensive approach to bloodmobile location selection for resilient BSCs.Design/methodology/approachThis study provides a novel integration of the spherical fuzzy analytical hierarchy process (SF-AHP) and spherical fuzzy complex proportional assessment (SF-COPRAS) methodologies. In this framework, the criteria are weighted using SF-AHP. The alternatives are then evaluated using SF-COPRAS, employing criteria weights obtained from SF-AHP without defuzzification.FindingsThe results show that supply conditions and resilience are the most important criteria for a bloodmobile location selection. Additionally, the validation analyses confirm the stability of the solution.Practical implicationsThis study presents several managerial implications that can aid mid-level managers in the BSC during the decision-making process for bloodmobile location selection. The critical factors revealed, along with their importance in choosing bloodmobile locations, serve as a comprehensive guide. Additionally, the framework proposed in this study offers decision-makers (DMs) an effective method for ranking potential bloodmobile locations.Originality/valueThis study presents the first application of multi-criteria decision-making (MCDM) for bloodmobile location selection. In this manner, several aspects of bloodmobile location selection are considered for the first time in the existing literature. Furthermore, from the methodological aspect, this study provides a novel SF-AHP-integrated SF-COPRAS methodology.

Application of Multi-Criteria Decision-Making in Leaf Spring Manufacturing’s Performance

Lean manufacturing is the optimal way of producing goods through the removal of waste and implementing flow, as opposed to batch processing. Many factories have transformed to align with the goal of lean manufacturing by minimising the resources of factories, such as less worker effort, less time and many more to lead to high efficiency towards good product quality and become highly responsive to customer demand. The condition of product and machinery, arrangement of inventory and equipment, the standard operation procedure of work and workers' safety awareness are the dominant elements in the leaf spring manufacturing process. Due to the crucial role that leaf springs play in the performance and safety of vehicles, it is crucial to eradicate any flaws in the designing and manufacturing processes. This study focuses on 5 core criteria, which are workers, time, safety, machines, and products that need to be enhanced. In the subgroup, each pair of sub-criteria will be compared regarding their importance with respect to each criterion. Analytical Hierarchy Process (AHP) is proposed to rank and aggregate the criteria based on their level of importance. The outcome of AHP showed that Safety (0.233) and Time (0.281) were the prominent criteria that need to be prioritised. Wear Personal Protective Equipment (PPE) (0.394), First Aid (0.324), Die and Pin (0.347), and Forklift Deliver (0.368) are the sub-criteria for safety and time. As a result, prompt and precise actions are needed to increase the quality and reliability of the product.

A new exponential knowledge and similarity measure with application in multi-criteria decision-making

The knowledge measure of fuzzy sets (FSs) has drawn greater attention and is still unresolved since it is the complementary idea to fuzzy entropy. The amount of knowledge is important in evaluating fuzzy information. This study proposes an exponential entropy-based knowledge measure for fuzzy sets to quantify the knowledge amount conveyed by fuzzy sets. Intuitive analysis of the characteristics of the knowledge amount in fuzzy sets is introduced, and its value and validity are demonstrated with numerical examples. In addition, a new measures is proposed from the exponential knowledge measure (i.e., exponential similarity measure). These measure are examined for validity, and their characteristics and put forward. Last, a modified Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) strategy based on the suggested similarity measure is suggested to handle a multi-criteria decision-making problem in a fuzzy environment. The effectiveness of the proposed approach is shown By utilizing a numerical example. A comparative analysis is also provided to evaluate the viability of the proposed approach.

Application of the new hybrid model LMAW-G-EDAS multi-criteria decision-making when choosing an assault rifle for the needs of the army

The paper addresses the selection of the most favorable alternative in the form of assault rifles to meet the requirements arising from modern combat operations. The complexity of the problem, conditioned by the different structural elements of automatic rifles and the specific situations of their use, has caused the application of Multi-Criteria Decision-making (MCDM) methods. A hybrid model was developed to guide the selection of the appropriate automatic rifle. The criteria were defined by experts, where the calculation of the weight coefficients of criteria was performed using the LMAW method Employing the grey EDAS method for MCDM, the study identifies an assault rifle that offers the most advantageous capabilities for carrying out firing tasks in the context of daily combat operations, with the aim of equipping the armed forces and raising the operational capability of the units. The validity of this model was verified through sensitivity analysis involving the adjustment of criteria weight coefficients.

Supplier Selection in the Age of Industry 4.0: A Review on MCDM Applications and Trends

The advent of Industry 4.0 has triggered a profound transformation in manufacturing and supply chain management, necessitating the adaptation of supplier selection processes to this evolving technological landscape. This comprehensive review paper places a significant focus on the role of multi-criteria decision-making (MCDM) methodologies and emerging trends in the context of supplier selection within Industry 4.0. It underscores the critical importance of effective supplier selection in achieving operational excellence and bolstering supply chain resilience in this new era, exploring the challenges and opportunities presented by technological advances such as the Internet of Things, big data analytics, artificial intelligence, and advanced manufacturing techniques. The paper looks into the theoretical underpinnings of MCDM techniques, highlighting their suitability for addressing the complex, multi-dimensional criteria associated with supplier selection. As a valuable resource, this study caters to researchers, practitioners, and decision-makers navigating the intricate landscape of supplier selection within the dynamic area of Industry 4.0, emphasizing the pivotal role of MCDM methodologies and the ever-evolving dynamics shaping supplier selection processes in the digital age.

Reckoning the performance of management institutions – A Mamdani fuzzy inference system approach

PurposeThe purpose of this research is to present an integrated methodological framework to aid in performance stewardship of management institutions according to their strategies based on a holistic evaluation encompassing social, economic and environmental dimensions.Design/methodology/approachA Mamdani fuzzy inference system (FIS) approach was adopted to design the quantitative models with respect to balanced scorecard (BSC) perspectives to demonstrate dynamic capability. Individual models were developed for each perspective of BSC using Mamdani FIS. Data was collected from subject matter experts in management education.FindingsThe proposed methodology is able to successfully compute the scores for each perspective. Effective placement, teaching learning process, faculty development and systematic feedback from the stakeholders were found to be the key drivers for revenue generation. The model is validated as the results were well accepted by the head of the institution after implementation.Research limitations/implicationsThe model resulting from this study will assist the institution to cyclically assess its performance, thus enabling continuous improvement. The strategy map provides the causality of the objectives across the four perspectives to aid the practitioners to better strategize. Also this study contributes to the literature of BSC as well to the applications of multi-criteria decision-making (MCDM) techniques.Originality/valueMamdani FIS integrated BSC model is a significant contribution to the academia of management education to quantitatively compute the performance of institutions. This quantified model reduces the ambiguity for practitioners to decide the performance levels for each metric and the priorities of metrics.

Selection and thermophysical assessment of phase change materials (PCMs) for space cooling applications in buildings

Phase change materials are gaining more attention in building comfort applications because of their latent heat thermal energy storage (TES) capacity. Identifying the best PCM candidate is a pivotal factor that significantly impacts the thermal performance of a building. This study delves into assessing prospective PCM candidates for potential utilization in cooling systems within buildings in hot subtropical climates. Extending the application of multicriteria decision-making (MCDM) methodologies, this research scrutinizes various commercial PCMs by conducting an exhaustive analysis of pertinent literature in the context of this specific application objective. Thermophysical properties are integrated into the MCDM framework to identify the most fitting candidates with optimal properties and attributes. The properties and attributes of PCMs are subjected to scoring and weighting through the AHP based on their significance in the given application context. TOPSIS and VIKOR techniques select the suitable PCM from the identified PCMs. The results showed that latent heat receives the highest weightage, amounting to 50.2%, due to its paramount importance. Furthermore, OM37 emerged as a promising choice for building space cooling, considering the prescreened temperature range of 30 °C–40 °C and for the specific location under consideration. Following PCM selection, thorough characterization was performed to evaluate the suitability of the chosen PCM for integration within building envelopes. The thermal conductivity of OM37 was determined to be 0.20 W/mK, while the morphology by a Field Emission Scanning Electron Microscope (Fe-SEM) intricate porous structure. Furthermore, a differential scanning calorimeter (DSC) suggests melting and solidification temperatures of 40 °C and 34 °C with a total enthalpy of 197.04 j/g, and a Thermogravimetry Differential Thermal Analysis (TG/DTA) showed a substantial weight loss of approximately 98.9% at around 247.3 °C. The presented experimental test results agree with the literature data and other researchers’ results.

Incorporating visibility information into multi-criteria decision making (MCDM) for wind turbine deployment

Wind turbines with taller hubs and longer blades are more feasible and cost-effective than their predecessors since they reduce the unit cost of energy production. However, the larger size of these structures makes them more visible and dominant features in the landscape. Higher visibility of wind turbines generally raises economic and environmental concerns in communities. The increasing size of wind turbines, therefore, poses a dilemma between lower costs of wind energy and higher visibility impacts. Most MCDM applications highlight the importance of wind turbine visibility and conceptualize this factor as the distance from settlements, coastal areas, etc. They assume that the higher distance from a potential turbine site lowers the impact of visibility or vice versa. This assumption helps introduce visibility impacts into the MCDM to some degree. However, calculating visibility can provide more reliable and realistic geospatial information to be used as a decision variable. This paper conceptualizes turbine visibility as quantitative visibility scores derived from multiple viewshed calculations. Geospatial information on visibility, capacity factor, land cover, topographic ruggedness, slope, and eight other distance criteria (e.g., distance from settlements) were processed in a GIS environment. Fuzzy standardization and the analytic hierarchy process (AHP) were used to standardize the maps and calculate criteria weights. A suitability map was produced by combining the weighted maps. Policy recommendations were made for wind power deployment.

Retracted: Spherical Cubic Fuzzy Extended TOPSIS Method and Its Application in Multicriteria Decision-Making

Retracted: Spherical Cubic Fuzzy Extended TOPSIS Method and Its Application in Multicriteria Decision-Making

A new intuitionistic fuzzy correlation coefficient approach with applications in multi-criteria decision-making

The Intuitionistic Fuzzy Set (IFS) is a powerful extension of Fuzzy Set (FS) used to handle vagueness and uncertainty. The correlation coefficient is an established tool for finding the strength of relationships between two IFSs. This study proposes a new approach for finding a correlation coefficient to compare with the existing approach and show its superiority over the existing approach. In many counter-intuitive cases, existing approaches fail to handle the problem appropriately by giving indeterminate form, incorrect and inaccurate results. We demonstrate the reliability and efficiency of the proposed approach in handling these concerns. We also present the application of the proposed approach in pattern detection, medical illness diagnosis, clustering, and Multi-Criteria Decision-Making (MCDM) to further exhibit its practicability and effectiveness.

Evaluating the skills of the CMIP5 global climate models using multicriteria decision-making analysis in Ethiopia

This study evaluates the skills of 30 CMIP5 GCMs and the Multimodel Ensemble (MME) in reproducing the characteristics of observed precipitation (Pr), minimum (Tmin), and maximum (Tmax) temperature over the Middle Awash sub-basin (MASB) in Ethiopia. The MME of the climate variables was generated using the simple arithmetic mean method. The entire analysis was performed on the raw historical GCM simulations (before bias correction) and observed data for the periods 1981–2005 based on monthly and annual time series data over the annual and seasonal temporal resolutions. This study considered two approaches. The first one was an evaluation of GCMs employing five statistical performance metrics (SPMs), i.e., mean, CV, PBIAS, RSR, and r. The second approach involves the application of multicriteria decision-making (MCDM) analysis, adopting three SPMs (PBIAS, RSR, and r). The relative weights of the three metrics were determined by the entropy method. Besides, the weighted average and compromise programming techniques were employed to rank and select the best-performing GCMs. The findings from the first approach using five SPMs demonstrate that, for a given variable of interest, a GCM that performs well for one SPM may fail to produce the same for another SPM on the same temporal scale. Likewise, for the same SPM at different resolutions, a GCM may perform well for a one-time scale but poorly for another. These suggested that the results of GCM skills relied mainly on the SPM, time scale, and data formats chosen for analysis. Hence, it is critical to comprehensively evaluate the skill of GCMs using multiple performance metrics over a range of spatial and temporal settings and data formats. In addition, results of the MCDM analysis proved that the ensemble of GCMs, which provide adequate performance in simulating the salient features of Pr, Tmin, and Tmax concomitantly across the MASB, encompass CMCC-CMS, BCC-CSM1.1(m), CMCC-CM, BNU-ESM, CanESM2, and MPI-ESM-MR. However, it was observed that different GCMs performed much differently in characterizing various variables over a range of temporal scales and data formats. The MME also proved its superior potential in duplicating the climate of the study area over several individual GCMs. The overall findings attested that instead of aggregating the ranks from the three variables into one, it is recommended to treat each variable independently while developing a subset of best-performing GCMs for ensembling since each GCM responds differently to each variable under a set of conditions. Finally, the approaches and findings from this study will be valuable input for subsequent climate and hydrologic studies in the study area and beyond.

A combined interval TOPSIS with multiple sensitivity strategies decision-making framework

Reasonable water resources management is critical for promoting the sustainable development of social economy. In the real world, water managers often work in an uncertain environment, and this uncertainty comes from inaccurate information related to water resource data. Therefore, there is uncertainty about the value of criteria in multi-criteria decision making (MCDM) and evaluation of water resources management. In addition, the robustness of multi-criteria decision-making evaluation based on uncertain data is difficult to quantify, which poses challenges to the application of MCDM in water resources management. Therefore, this paper proposes a decision-making framework combining interval TOPSIS and a multi-sensitivity strategy. The framework is used for robust water resources management under uncertain conditions, revealing the optimal solution under the influence of uncertainty and sensitivity strategies, and identifying the ranking change mechanism by revealing the threshold of each criterion to identify alternatives as the optimal solution. The applicability of the proposed framework is verified in different cases (including water resources allocation and reservoir flood control operations). The outcomes indicate that: (1) the proposed framework expands the capabilities of current methods and provides a potential approach to deal with the robustness of options identified by decision makers engaged in water resources management under uncertainty; (2) among the proposed sensitivity strategies, the strategy of changing one or more criteria of a single scheme is more realistic in a changing environment; (3) in the case analysis, two cases show that changing from the lower position to the first position requires 80% and 45% of a set of criteria values. The findings of this study will provide a scientific basis for water resources managers to make robust scheme decisions.

Application of Multi-Criteria Decision-Making Methods in Warehouse: A Brief Review

This review paper investigates the application of various multi-criteria decision-making (MCDM) methods in the context of warehouse management, considering papers published from 2010 to date. Warehouses often face many challenges, including efficient inventory management, space optimization, proper resource allocation, and optimal supplier selection. This paper focuses on several well-known MCDM methods that are often used in the context of warehouse management. Full consistency method (FUCOM), analytic hierarchy process (AHP), the technique for order of preference by similarity to ideal solution (TOPSIS), weighted aggregated sum product assessment (WASPAS), criteria importance through intercriteria correlation (CRITIC), measurement of alternatives and ranking according to the compromise solution (MARCOS), best worst method (BMW), evaluation based on distance from average solution (EDAS), correlation coefficient and the standard deviation (CCSD), indifference threshold-based attribute ratio analysis (ITARA), and simple additive weighting (SAW) are some of the methods reviewed in the paper, as well as certain fuzzy versions of the methods. This review paper provides a brief comprehensive overview of the application of these methods in the context of warehouse management. Data collection leads to results that tell us that the methods are mainly used in solving problems during the selection of warehouse location, the selection of warehouse equipment, and also in the management of the warehouse itself and the performance of its management. It has also been seen that the methods are useful even in "green" logistics, as well as in inventory management.