Multi-criteria Evaluation Research Articles

Многокритериальный подход к отбору вариантов создания сети железных дорог

The article provides a multivariate approach to the selection of options for the outline of a network polygon in a poorly developed area. When developing deposits of natural resources, it is necessary to qualitatively carry out a comprehensive assessment of the sustainability of the development of the relevant region and develop strategies for its development. An underdeveloped area can be classified as a problem region, which includes underdeveloped or depressed areas. By underdeveloped areas (regions), the authors understand the territories of a large area inhabited by a small population, poorly developed or completely absent railway network of communication routes on the one hand, and on the other, there are rich reserves of deposits of natural resources that cannot be fully exploited. To assess the prospective development of the railway network in such areas, taking into account its socio-economic development, it is proposed to use a multi-criteria approach. The main provisions of the methodology for the formation of options for creating a railway network using graph theory and their consistent multi-criteria evaluation are presented. A specific calculation example is given, showing the efficiency of the proposed methodology

Developing a tile drainage module for the Cold Regions Hydrological Model: lessons from a farm in southern Ontario, Canada

Abstract. Systematic tile drainage is used extensively in poorly drained agricultural lands to remove excess water and improve crop growth; however, tiles can also transfer nutrients from farmlands to downstream surface water bodies, leading to water quality problems. Thus, there is a need to simulate the hydrological behaviour of tile drains to understand the impacts of climate or land management change on agricultural surface and subsurface runoff. The Cold Regions Hydrological Model (CRHM) is a physically based, modular modelling system developed for cold regions. Here, a tile drainage module is developed for CRHM. A multi-variable, multi-criteria model performance evaluation strategy was deployed to examine the ability of the module to capture tile discharge under both winter and summer conditions (NSE > 0.29, RSR < 0.84 and PBias < 20 for tile flow and saturated storage simulations). Initial model simulations run at a 15 min interval did not satisfactorily represent tile discharge; however, model simulations improved when the time step was lengthened to hourly but also with the explicit representation of capillary rise for moisture interactions between the rooting zone and groundwater, demonstrating the significance of capillary rise above the saturated storage layer in the hydrology of tile drains in loam soils. Novel aspects of this module include the sub-daily time step, which is shorter than most existing models, and the use of field capacity and its corresponding pressure head to provide estimates of drainable water and the thickness of the capillary fringe, rather than using detailed soil retention curves that may not always be available. An additional novel aspect is the demonstration that flows in some tile drain systems can be better represented and simulated when related to shallow saturated storage dynamics.

Looking for the surviving optimal areas for the threatened species Pinna nobilis in a highly anthropized coastal lagoon (Mar Menor, SE Spain)

Pinna nobilis, an endemic bivalve species in the Mediterranean Sea, is critically endangered mainly due to the devastating impact of the protozoan parasite Haplosporidium pinnae. The population within the Mar Menor lagoon (Murcia, Spain) represents one of only two surviving populations along the Spanish coast. This relict population has witnessed a significant decline since 2016, primarily due to eutrophication episodes and other anthropogenic impacts affecting the lagoon. It is imperative to identify the most suitable zones for the survival of this species, where adult individuals could be translocated from affected areas to enhance their chances of survival. In the present study, we identify these zones through a Multi-Criteria Evaluation considering several factors that pose a threat to the species. This evaluation was complemented using Geographic Information Systems based multi-criteria decision analysis (GIS-MCDA). A total of 18 factors were weighted and combined, resulting in a surface area of 307.92 hectares (2.28% of the lagoon) with over 70% high suitability for species survival.

Assessment of Physical, Social, and Economic Vulnerability to Landslides Disaster in the Karangsambung Karangbolong National Geopark, Indonesia.

Abstract The Karangsambung-Karangbolong National Geopark (GNKK) is administratively located in Kebumen Regency, Central Java Province, Indonesia. The GNKK area has an area of 543,599 km2 which includes 12 sub-districts with 117 villages. The morphology of the GNKK area consists of hills, valleys, and plains to the coast. The morphology of hills and mountains is an area that is prone to landslides. Assessment of physical, social, and economic vulnerability needs to be carried out so that disaster risk analysis and mitigation can be carried out in the future. The aims of this study are 1. To determine the spatial distribution of physical, social, and economic vulnerabilities in the Karangsambung Karangbolong National Geopark Area, 2. To analyze the physical, social, and economic vulnerability to landslides in the Karangsambung Karangbolong National Geopark Area. Assessment of physical, social, and economic vulnerability using the Spatial Multi-Criteria Evaluation (SMCE) method. The results of the main study of the GNKK area have high, moderate, and low classes of physical, social, and economic vulnerability to landslides. However, most GNKK areas are classified as moderate. The community’s social conditions in each village significantly affect the areas prone to frequent landslides. The strategy for disaster mitigation by a landslide is increasing human resources for disaster knowledge with disaster mitigation training and using infrastructures such as installing landslide-prone signs and trigger lines.

Areas with agricultural suitability for corn cultivation State of Mexiconcy

Ensuring access to food as a priority of the sustainable development objectives requires immediate attention to crops; motivated by this, the present study shows the results of the identification of agricultural suitability zones, specifically in the cultivation of corn in the State ofMexico, using the multi‑ c riteria evaluation (MCE) that allows tomodel the territorial reality and execute the spatial process with the most important variables in the growth those crops. The identification of the processes and their regional problems gave guidelines for the weighting of each of them and define their criteria for the optimal growth of the plant. The study was carried out with the assignment of weights to the variables of altitude, temperature, precipitation, slopes and edaphology according to research on their degree of influence and dependence among them; the result is the areas with the greatest agricultural suitability for the cultivation of corn in the State of Mexico (with restriction of protected natural areas and urban areas), with a timely verification of the already existing crops and improve decision making by expanding the territory with the greatest probability of optimization and crops’ yield. This methodology proposal is intended to be replicable to other crops and/or areas in which the processes and patterns that modify the characteristics of areas from a crop to high yield are recognized.

The efficiency assessment of using hybrid neural networks for the detection of forged audio data in socially oriented systems

The subject of the research is the problem of detecting falsified data, in particular in audio format, in socially oriented systems. The goal of the work is to develop an effective model based on recurrent and convolutional neural networks for determining the fact of forgery of sound data, using MapReduce technology for parallelization. The article addresses the following tasks: determining the features of audio in socially-oriented systems, conducting an analysis of algorithms for processing audio information both in the form of text and in the form of a signal, forming a list of target architectures of neural networks and revealing the features of their implementation, conducting an experimental test of effectiveness selected approaches. The following methods used are – analytical and inductive method for determining the target set of neural network architectures; expert assessment for the formation of the most influential efficiency factors; experimental, multi-criteria evaluation and statistical methods of data augmentation to determine the most effective model. The following results were obtained: an audio data reprocessing algorithm was developed for the possibility of using recurrent and convolutional networks. Several approaches to data classification using augmentation based on vector autoregression and MapReduce parallelization technology have been implemented. It was determined that the most effective model for the multi-criteria selection problem is a combination of a bidirectional recurrent neural network with support for short- and long-term memory with several convolutional networks. The advantages of using MapReduce technology to optimize training time and data processing are shown, and a set of open questions for further research and applied implementation is defined. Conclusions: he application of an analytical and inductive approach followed by experimental verification made it possible to develop an effective (with an accuracy of more than 96%) a mechanism for detecting fabricated data both in the form of a signal and in text form. The obtained result makes it possible to assert the feasibility of implementing the proposed approach, and, accordingly, makes it possible to reduce the influence of such information in socially oriented systems, especially during crisis events.

Methodology of evaluating finished goods warehouse performance through lean methods

This paper considers the problem of evaluating the effectiveness of the finished goods warehouse of a manufacturing company, in which a modified TPM method - Total Productive Management (TPM2) - was applied to improve productivity. A multi-stage methodology was proposed, including a decision to modify the system, determination of the scope of changes, monitoring the results obtained and a multi-criteria evaluation of the changes made. The decision to make modifications to the existing system was motivated by the lower-than-expected quality of customer service (frequent delivery delays). With regard to the transport department, lean flow pillar activities were focused on analysing losses (muda) in warehouse processes (product loading and package unloading). The purpose of these activities was to minimise interruptions in warehouse processes (product loading and package unloading). "The steps for solving the problem" methodology based on Deming's PDCA cycle was used to solve the problem. The analysis covered, among other things, the information flow processes between production planning and the customer service department, the planning processes of the dispatcher, the efficiency of the loading processes, and the causes of interruptions in warehouse operations. The analyses employed the chronometry of selected works, the 5W + 1H method and the Pareto method. By using the 5S method and some characteristics of the SMED method, the organisation of loading work was decisively changed (shunting yard changes, appropriate buffers for transport equipment). The changes introduced in the system were monitored for several months. Appropriately defined OEE indicators were used to assess the behaviour of the system after the changes. The indicators consider the use of available warehouse time, the efficiency of the loading process and the quality of the tasks performed. The results that can be achieved are presented using the specific example of the finished goods warehouse of a manufacturing company in the FMCG sector.

Multivariate efficiency assessment and optimization of unitized regeneration proton exchange membrane fuel cell based CCHP system

Targeting the shortcomings of low round-trip efficiency (RTE) in unitized regeneration proton exchange membrane fuel cell (UR-PEMFC), a model incorporated combined cooling, heating, and power (CCHP) technology for UR-PEMFC was proposed, which integrated a three-dimensional two-phase flow field model with a zero-dimensional system model. Additionally, a multi-criterion evaluation system was introduced for the URFC-CCHP system, which encompasses three decision-making methods. To illustrate the applicability of the model, the assessments of four typical flow field configurations were utilized as case studies and presented their rankings. The results reveal that, compared to a system focused on electrical power output, the system exhibited a remarkable enhancement in RTE, increasing from 35.96 % to 76.67 %. Notably, during the cold season, the RTE surpassed that of the warm season by 8.74 %–10.62 %. Operating under a cyclic condition of fast charging and slow discharging proved to be conducive to maintaining the optimal RTE of the system. Furthermore, the computational outcomes of the three decision-making methods in the multi-criterion evaluation system exhibited consistency, unanimously identifying the optimal flow field as the three-serpentine flow field, while designating the single-serpentine flow field as the least favorable. It aims to present a novel technology for enhancing the RTE of UR-PEMFC.

Heritage Evaluation of the Carob Tree MTAS in the Territory of Valencia: Analysis and Social Perception of the Ecosystem Services and Values from Cultivating It

The concept of Multifunctional Territorialized Agrifood Systems (MTASs) arose as an alternative to global hegemonic models in the 21st century. This study intends to identify the main ecosystem values and services generated by the MTAS of the carob tree in the territory of Valencia, which is one of the most characteristic dryland fruit tree species farmed in the Mediterranean. To do so, a multi-criteria quantitative evaluation system has been used that enables values to be assigned to the kinds of significance placed on MTASs. For this purpose, a questionnaire was carried out with 268 local inhabitants. The global score obtained is 7.6 points, indicating a high heritage value. Some of the criteria with the best scores are related to the authenticity of the carob tree and its social and historical values since this crop is a testament to ancestral techniques and traditions. Furthermore, this Mediterranean crop provides numerous ecosystem services and has multiple properties and applications, mainly in the food and pharmaceutical industries. The local population has scored the vulnerability value with only 4.1 points as a consequence of the progressive abandonment of the cultivated area in recent decades. Therefore, greater involvement from social stakeholders is essential in order to preserve this crop.

A Multi-Criterion Evaluation Process for Determining Cost-Effective Harvesting Systems in Fragmented Boreal Forests

Nordic forests, like those found in Canada, used to consist of large and relatively homogeneous mature stands. Such a spatial pattern allows for harvest operations to be highly concentrated, minimizing procurement costs. However, the growing fragmentation of these forests makes planning difficult and increases the costs of road building and machinery relocation. While operational solutions have been developed in regions with small harvest areas, their transferability to different settings is unknown. Finding the most suitable combination of equipment for a given context is challenging considering the multitude of possibilities. The objective of this study is to identify, from all possible options, a subset of harvest systems expected to perform well in fragmented boreal forests. The results from this research are two-fold. First, a comprehensive review of forest machines and harvest systems is provided. Second, a multi-criteria decision analysis (MCDA) methodology is proposed to evaluate the alternatives. In a boreal forest context, the conventional harvester-forwarder system (CTL) was ranked among the best solutions, along with mild adaptations of the usual configurations. Several whole-tree (WT) system configurations were also highly ranked. While the results are specific to the case studied, the review and selection methodology can serve in different operational contexts.

Análisis de los peligros hidrometeorológico y caída de roca en la ciudad de Pucalá y CP Huaca Rajada y Sipán

The objective of the research is to develop an analysis of the hydrometeorological and rockfall hazards that impact the city of Pucalá and the populated centers of Huaca Rajada and Sipán, based on multi-criteria evaluation (MCE) techniques, where the variables of the susceptibility of the territory and the evaluation parameters for fluvial flooding, flooding, debris flow and rockfall hazards are identified. In addition, a matrix is used to assign weightings according to the relative importance of each variable and its descriptors with respect to the probability of increasing hazard levels. The variables and descriptors correspond to information obtained from sources of public and private entities and from field observations where the lithology, morphology and slope variables were validated as conditioning factors of the hazards, and with data from the Sipán station, maximum precipitation is obtained as a triggering factor. The hazard is related to a critical scenario for pluvial flooding (flooding) that presents maximum precipitation thresholds and affects the city of Pucalá, and another for fluvial flooding where there are sectors with exposure due to the overflowing of the Chancay River and irrigation canals. Meanwhile, the critical scenarios for rockfall and debris flow hazards occur in sectors where there are unstable conditions on the slopes of hills and mountains of Caballo Blanco hill and affect the local road that connects with other towns, and in sectors of alluvial-torrential material deposition where the town of Sipán is located.

Multi-criteria evaluation of poly-generation system applied to commercial buildings with various prime movers and building types

The present study evaluates the performance of a poly-generation system applied to commercial buildings. An internal combustion engine (ICE) and solid oxide fuel cell (SOFC) used as prime movers represent different efficiency distributions according to part load ratio variation. Accordingly, discrete results are found in terms of energy, environment, and economy depending on the prime mover type applied to each building. A renewable energy system is combined with the poly-generation system, and the outputs produced from the energy generation units are transferred to the energy storage system and supplied to the demand sources. Through the parametric study and hybrid control method, the stored energy is optimally distributed to the cooling and heating system to maximize the primary energy saving ratio. The major components constituting the poly-generation system are modeled and validated based on experiments and literature to enhance the reliability of the dynamic simulation model. The monthly amounts of replenished and wasted energy are examined, and the magnitude of produced energy contribution to the building self-sufficiency ratio is also identified. When ICE- and SOFC-based poly-generations are applied to the hospital, 30.2% and 45.2% of the primary energy consumption is saved, respectively, compared with the conventional system. For the office, the corresponding systems reduce primary energy consumption by 1.8% and 37.2%, respectively. The economic feasibility of the poly-generation systems is examined considering the current energy project in South Korea.

An Overview of Image Steganography Techniques: Historical Development, Methodologies, and Evaluation Criteria

This paper provides a detailed overview of image steganography, tracing its historical roots and examining the development of modern techniques. Steganography, derived from the Greek words "stegos" (cover) and "graphia" (writing), refers to the practice of concealing information within a host medium. Historically, steganographic techniques included tattooing hidden messages and using invisible ink, but the digital age has introduced new possibilities for secure data embedding, particularly within images. With the advent of the internet, the need for robust steganographic techniques has increased, leading to advancements in both spatial and frequency domain methods, including Least Significant Bit (LSB) replacement, Discrete Cosine Transform (DCT), and wavelet-based techniques. This paper also reviews evaluation criteria such as Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE), and Structural Similarity Index Measure (SSIM) to assess the effectiveness of various steganographic methods in achieving high security, capacity, and imperceptibility. Challenges such as balancing these criteria, developing multi-criteria evaluation tools, and optimizing embedding processes are highlighted. This review aims to provide insights into current advancements, limitations, and future directions for research in image steganography.

Predicting urban tomorrow: CA-Markov modeling and district evolution

The global population is experiencing exponential growth, resulting in a substantial increase in urbanization and subsequent urban expansion. This uncontrolled expansion, often termed urban sprawl, poses significant challenges to sustainable urban development. Understanding the importance of this concern, obtaining precise information about changes in Land Use/Land Cover (LULC) becomes crucial. This research examines the transformative processes of LULC and urban expansion over a 20-year period in two distinct study areas. For this purpose, built-up areas are first analysed using satellite-derived land surface temperature data, revealing temperature increase over time attributed to urban expansion. To project future trends using CA-Markov model, the suitability maps for each LULC class aggregated through the Multi Criteria Evaluation (MCE) method. Subsequently, the CA-Markov simulates the LULC maps for 2017 and 2018 for each study area, with a focus on the year 2050. Model calibrated by comparing the simulated maps with the actual maps in both study areas, and the reliability is affirmed by high Kappa coefficients (> 80%). Consequently, the study predicts LULC maps for 2050, revealing that both areas will experience a continued increase in built-up areas, a decrease in forested areas, and a relative stability in agricultural zones over the next 33 years.

An Integrated Building Information Modeling and Life-Cycle Assessment Approach to Facilitate Design Decisions on Sustainable Building Projects in Canada

In the context of the digital and sustainable transformation of building projects, the integrated approach of Building Information Modeling (BIM) and life-cycle assessment (LCA) has been widely studied. Recent advancements in such integrated modeling processes and techniques have not yet provided reliable and robust decision-making capabilities for designers to intuitively choose between material alternatives. This study develops a new design framework that integrates BIM, LCA, and multi-criteria decision-making (MCDM) algorithms to facilitate sustainable design processes in building projects. A case study using a single-family housing project in the British Columbia province of Canada was implemented to test the designs to demonstrate the effectiveness of the proposed integrated framework, including a three-way comparison of design scenarios—conventional hot-roll steel, recycled steel, and timber. The results indicate a significant performance improvement with the adoption of recycled structural steel materials, surpassing conventional steel designs and demonstrating a similar performance to that of timber designs. The study underscores the importance of informed decision-making in material selection, driven by the quantitative analysis of digital designs and multi-criteria evaluation (e.g., social carbon cost). This integrated framework offers a valuable tool for designers, engineers, and builders to achieve sustainability when designing building projects through the systematic and rapid comparison of environmental performance.

Using cellular automata and multi-criteria evaluation to simulate the wildfire expansion in Prince George, British Co-lumbia

Wildfires pose a critical and ongoing challenge in British Columbia, Canada, threatening human life, property, and natural ecosystems. To understand and predict the behavior of such fires, our study employs Cellular Automata (CA), a mathematical model adept at simulating complex systems through grid-based cell interactions. This model, validated by prior research, incorporates a wind propagation rule that significantly enhances the prediction of wildfire spread in the direction of prevailing winds. Research centers on a wildfire event in Prince George, utilizing CA to simulate fire dynamics influenced by var-ious factors. The models strength lies in its ability to represent detailed local interactions and its flexibility in scenario testing, which is instrumental in understanding model uncer-tainties. By simulating different fire scenarios, the study aims to grasp the complexities and potential variables affecting wildfire behavior. The research provides a foundation for decision-makers to analyze and study wildfire events, leveraging a Multi-Criteria Evaluation (MCE) Model to assess the susceptibility of cells to fire. This comprehensive approach combines CA with MCE, offering a robust framework for simulating and manag-ing wildfire expansion in British Columbia.

Recent advances in digital image masking techniques Future challenges and trends: a review

Image steganography has advanced over recent decades, driven by a demand for secure, high-capacity data-hiding techniques capable of maintaining imperceptibility in digital images. This study provides a comprehensive review of steganographic techniques, highlighting recent improvements across spatial and frequency domains and innovations that integrate cryptographic methods, genetic algorithms, and machine learning to enhance security and payload capacity. The assessment reveals trade-offs between imperceptibility, capacity, and security in various methods, including least significant bit (LSB) substitution, frequency domain transformation, edge detection, and pixel intensity manipulation. This analysis identifies key research gaps in multi-criteria evaluation, PSNR reliability, and the need for enhanced methodologies in imperceptibility and robustness to withstand statistical and steganalysis attacks. By investigative these trends, this research emphasizes the importance of complementary image quality and data safety to improve effective and resilient stenographic systems.

A Research on Determining the Importance Levels of Criteria Effective in Forest Road Network Planning through GIS-Based Methods

This study investigated the importance levels of criteria effective in forest road network planning using Geopraphic Information System (GIS)- based Multi- Criteria Evaluation (MCE) method. It is crucial to determine the criteria to be considered in forest road construction and planning for a standardized application nationwide. The research was conducted within the boundaries of the Yaylacık Forest Management Directorate (YFMD) under the Tokat Forest Management. Firstly, the existing road network was identified in the research. After the identification of the existing road network, a GIS database was created. In this study, criteria to be used, in Forest Road Network Planning (terrain slope, aspect, road density, distance to road, land use, distance to main stream) were determined. Each criterion was classified and scored internally. Information from road and road network planning studies and previous works were utilized in determining the criteria to be used in Forest Road Network Planning. Five different degrees and suitability values are defined for the determined criteria. In this context, it was created to reach 5 fundamental road network planning functions to determine their positional statuses as Absence (Ab), Very Suitable Areas for road planning (VS), Suitable Areas for road planning (S), Less Suitable Areas for road planning (LS), and Very Less Suitable Areas for road planning (VLS). As a result, Terrain Slope and Road Density were determined as the most effective criteria in Road Network Planning, while Distance to Main Stream was identified as the least effective criterion. As a result of the study, a flow chart was created to determine the criteria and impact values that are effective in forest road network planning in order to ensure integrity and convenience in application throughout the country.

Multicriteria screening evaluation of geothermal resources on mine lands for direct use heating

Direct use of geothermal energy is the oldest and most versatile form of utilizing geothermal energy. In the last decade, this utilization has significantly increased, especially with the installation of geothermal (ground-source) heat pumps. Many current and inactive mine land sites across the U.S. could be redeveloped with clean energy technologies such as direct use geothermal, which would revitalize former mining communities, help with reducing greenhouse gas emissions, and accelerate the transition to a clean energy economy. We present a multicriteria screening framework to evaluate various aspects of direct-use geothermal projects on mine lands. The criteria are divided into three categories: (1) technical potential, (2) demand and benefits, and (3) regulatory and permitting. We demonstrate the framework using publicly available data on a national scale (continental U.S.). Then, using an example of abandoned coal mines in Illinois and focusing on resource potential, we illustrate how this evaluation can be applied at the state or more local scales when a region’s characteristics drive spatial variability estimates. The strength of this approach is the ability to combine seemingly disparate parameters and inputs from numerous sources. The framework is very flexible—additional criteria can be easily incorporated and weights modified if input data support them. Vice versa, the framework can also help identify additional data needed for evaluating those criteria. The multicriteria screening evaluation methodology provides a framework for identifying potential candidates for detailed site evaluation and characterization.

A Multicriteria Evaluation Based on the Grey-TOPSIS Method for Water Distribution Companies in Brazil

A Multicriteria Evaluation Based on the Grey-TOPSIS Method for Water Distribution Companies in Brazil