Multi-criteria Optimization Method Research Articles

Are the Nutritional Properties of Organic Tomatoes Altered by Single and Combined Microbial Soil Inoculants?: A Multiperspective Approach

AbstractBiologically active compounds are key-important ingredients of tomato fruits, especially those produced by organic agricultural practices. Being biologically effective soil treatments, microbial inoculants can improve soil quality through a variety of mechanisms. Their activity can influence soil properties and plant development, thereby determining the quantity and quality of the crop. However, little research was done on how these inoculants affect the nutritional quality of the tomato fruit and on the antioxidant status of the fruits. This study investigated lycopene content and total antioxidant capacity of organically grown tomato fruits (Solanum lycopersicum L. var. ‘Mobil’) using various types of single and combined bioeffector products in two growing seasons. Single inoculation contained Trichoderma harzianum, plant growth promoting Pseudomonas sp., and phosphorus-mobilizing Bacillus amyloliquefaciens strains. The combined treatment consisted of biotic Trichoderma harzianum, Pseudomonas fluorescens, and Bacillus subtilis strains with abiotic micronutrients of zinc and manganese. Sum of ranking differences method, as a multicriteria optimization method, was used to rank the treatments and identify the ones deviating the least from the reference treatment. The results showed that all microbial soil inoculants positively affected tomato lycopene content. The combined treatment showed significantly higher lycopene content than the Control in both years. We found that weather and climate conditions also greatly influence the total antioxidant capacity. Based on our results, we recommend the use of combined bioeffective treatments to improve the food quality value of tomato fruits.

Application of The Aggregation and Multicriteria Optimization Method in Assessing the Level of the Knowledge Economy of World Regions in Industry 4.0

The article proposes a new methodology for determining the level of the knowledge economy of countries in terms of the possibilities of using Industry 4.0 technologies. The relevance of the study is due to the transition to a new technological structure – “Industry 4.0” in the world. The aim of the study is to analyze data on the main sub-indices of the knowledge economy associated with Industry 4.0 for countries around the world based on the author’s methodology. As a tool for this analysis, the k-means++ clustering method was used to classify countries according to their characteristics. The assessment of the potential of Industry 4.0 is determined on the basis of 5 criteria characterizing various aspects of the development of countries at the level of economic knowledge. In the calculation process, determining the extent to which the indicators used describe the level of the knowledge economy, and the use of the aggregation formula and multi-criteria optimization, constitutes the scientific novelty of the study. It was concluded that as a result of clustering the countries of the world using the formula Aggregation and Multicriteria Optimization, the number of clusters decreased and the distribution of countries between clusters began to more adequately reflect reality. The results of the study can be used in the process of assessing the competitiveness of countries during the transition to the Industry 4.0 economy, as well as in developing strategies and concepts for countries.

Dry milling of stir-cast and heat-treated EV31A magnesium alloy: An experimental investigation based on the multi-criteria optimization method

The purpose of this study is to examine the impact of various milling parameters and sample preparation methods on the end-milling of EV31A Mg alloy under as-cast, T4, and T6 heat-treated conditions. The test specimens were prepared through stir-casting and heat-treated according to T4 and T6 conditions. The CNC vertical milling machine with the HSS tool was used for the end-milling process based on Taguchi's L9 orthogonal array. Three levels of variation are applied to the process parameters, including spindle speed (S), feed rate (f), depth of cut (d), and test specimen (as-cast, T4, and T6 EV31A). The parameters of surface roughness (Ra, Rz, Sa, Sz), the rate of material removal (MRR), and the cutting force (Fr) were similarly measured. For surface roughness, optical profilometry was used, while the weight loss method and dynamometer were employed, respectively, to assess MRR and Fr. In order to improve the process parameters, TOPSIS (techniques order preferences by similarity to ideal solution) is employed. This method reduces several responses to a single measurable response (the closeness coefficient). S = 1500 rpm, f = 150 mm/min, and aP = 1.5 mm are the ideal process parameters to achieve the maximum closeness coefficient (Ci) of 0. 917129 under as-cast circumstances. Furthermore, analysis of variance (ANOVA) verifies that sample preparation methods of 24.59 % and depth of cut of 38.19 % significantly impact response characteristics.

Analysis of scenarios for transforming the object "Ukryttya" into an environmentally safe system by the method of multicriteria optimization

Based on the criteria for comparative analysis of scenarios grouped into factors, the value of scenarios was determined using the multicriteria optimization methodology. The evaluation methodology includes indicators of weights of factor groups and weights of criteria for the relevant factors. Scenario value assessment is determined by calculating a generalized weighted additive function. It is used to rank the scenarios with the established parametric characteristics of the criteria. The results of the scenario assessment and their ranking are recommendations for making decisions on the sequence of scenario implementation.

A novel cost-palatability bi-objective approach to the menu planning problem with an innovative similarity metric using a path relinking algorithm

Bad eating habits are considered with low exercise, tobacco, and alcohol use, among the greatest health risk factors in high-income countries. Here, the spread of non-communicable diseases related to diet contrasts with the increasing availability of diet guidelines and health information. We are all left wondering, why are we not eating healthier? Palatability and cost appear as the two most important barriers to adherence to any prescribed diet. This work aims to generate high-adherence healthy menus attending to Mediterranean standards, modelling and solving a cost palatability bi-objective optimisation problem. Although the latter is implicitly considered in most current models, its use as a quantifiable objective is novel. For this, a novel Similarity Function is introduced, which evaluates the proximity of two different menus and returns a similarity metric between 0 and 1. A multi-criteria optimisation method is used to design nutritious menu plans and analyse the trade-off between the cost and palatability of menus. A Path Relinking algorithm is later applied to improve the objective values, with specific considerations to palatability, designing healthy menus that can beat those adherence barriers.

Multi-attribute decision making based on VIKOR with probabilistic linguistic term sets: An application to the risk evaluation of foreign direct investment.

The multiple global environments have triggered changes in the international environment, leading to a sharp decline of foreign direct investment (FDI) compared to pre-pandemic level. To evaluate the investment risk of FDI and make optimal investment decision becomes the most important issue for investors. This paper focuses on the evaluation of investment risk for FDI. First, an index system for risk evaluation of FDI is constructed. Then, we introduce the probabilistic linguistic entropy and cross entropy measures, based on which, a programming model is developed to identify the objective attribute weights. A composite weight derivation method, which takes both the objective attribute weights and the subjective attribute weights into account, is further introduced. In view of attributes' uncertainty and fuzziness and the conflicting characteristics of some attributes, the VIKOR (the Serbian name: VlseKriterijumska Optimizacija I Kompromisno Resenje, means multi-criteria optimization and compromise solution) method is used to evaluate the risk of FDI under the probabilistic linguistic environment. Furthermore, a case study is presented to illustrate the proposed method. The comparative analysis and some further discussions verify the validity of the proposed method for the FDI risk evaluation.

Information technology of synthesis of liquid dosing process control

Problem. Currently, different solutions are available on the global market for liquid dosing. There is no universal technology, as the same substances can be dosed using different types of equipment. Therefore, manufacturers face the complex task of determining the most optimal kind of equipment to achieve their goals. These issues are a complex multi-criteria scientific problem, and to effectively address them, it is necessary to develop a technology for synthesizing a liquid dosing control system using multi-criteria optimization methods in different conditions of information determinacy. Goal. The paper aims to increase the efficiency of liquid dosing control by developing information technology for the control system synthesizing. The object of the paper is the process of information technology development for synthesizing the liquid dosing control system. The subject of the paper is the models for the selection of hardware and software for the liquid dosing control system. Methodology. The study analyses and provides a classification of liquid dosing technology and analyses existing liquid dosing control systems. A structural model of information technology for synthesising a liquid dosing control system is developed, and criteria for selecting the elements of the liquid dosing control system are justified. A model for selecting PLC and SCADA systems for synthesising the liquid dosing control system is also developed using hierarchical analysis methods and multi-criteria evaluation and optimisation. Results. The paper resulted in the following: analysis and classification of liquid dosing technology; analysis of existing liquid dosing control systems; development of a structural model of the information technology of synthesising a liquid dosing control system; justification of criteria for selecting the elements of the liquid dosing control system, and the development of a model for selecting PLC and SCADA systems for the synthesis of the liquid dosing control system using hierarchical analysis methods and multi-criteria evaluation and optimisation. Originality. Further development of the methods of hierarchy analysis and multi-criteria assessment and optimization has been achieved by applying them to a specific field – the development of models for selecting hardware and software for the liquid dosing process control system. Practical value. The proposed information technology of synthesising a liquid dosing control system, as well as the mathematical models for selecting hardware and software for the liquid dosing process control system, will reduce the time and cost required to develop such a system.

Construction of Social Resilience Assessment System after Floods in the New Era

Abstract This paper constructs an assessment framework through theoretical research and literature study, determines the assessment indicators using the systematic review method, and forms a final assessment system of social resilience after flooding based on the correlation test. On this basis, the index weights were determined using the comprehensive assignment method, and the social resilience index was calculated using multi-criteria optimization and compromise solutions methods. The spatiotemporal evolution trend and spatial correlation characteristics of post-flood social resilience were explored by combining mathematical statistical methods, geographic information technology, and spatial measurement models. The temporal evolution characteristics of different dimensions of social resilience during the period 2012–2021 show that the social resilience index declined steeply in 2012, reached a maximum value of 0.316 in 2018, then gradually decreased to 0.305 in 2020, and recovered to 0.312 in 2021, with an overall increase of 5.05%. Assessing the social resilience of 17 cities under the jurisdiction of Henan Province, overall, the ability of the social system to cope with heavy rainfall and flooding disasters in 10 cities showed an increasing trend, and 7 towns showed a decreasing trend.The social resilience of Zhengzhou City under heavy rainfall and flooding disasters in 2017–2021 showed a trend of decreasing and increasing, with a composite index fit of 0.885, 0.893, 0.806, 0.893, 0.806, 0.824, 0.861.This paper constructs a social resilience assessment system after flooding to provide some reference for central cities to cope with extreme weather.

Analysis of the criteria selection problem in diversification models

The digitalization of the economy reduces the cost of doing business by automating the relevant processes, but any transformation creates new risks and economic instability. Economic instability leads to a drop in the standard of living and, as a result, negatively affects the activities of trade enterprises. Small and medium businesses are especially sensitive to any changes. The decrease in demand for most everyday goods has a painful effect on the activities of small and medium-sized businesses and leads to the emergence of new risks. These risks have a significant impact on reducing the profitability of enterprises. Therefore, it is important for each enterprise to diversify the activities of the enterprise, which includes the expansion of the product range, the reorientation of sales markets and the optimal distribution of goods between divisions of one enterprise. The subject of the article is multi-criteria models of a diversified portfolio that minimize the risks that arise in the era of the digital economy when managing retail chains. To formalize the problem, five models are proposed that differ in vector objective functions, both in the quantity and quality of the selected criteria. The aim of the work is to analyze the problem of choosing criteria in the corresponding multicriteria or vector diversification problems. The article examines the advantages of introducing an additional criterion of entropy maximization into the criteria of the classical two-criteria model of portfolio theory, which characterizes the degree of diversity of the portfolio composition. A complex combination of methods of classical portfolio theory and multicriteria optimization is applied. The results include a comparison of three methods for solving the following problems: criteria convolution, successive concessions, and computer simulation of the Pareto set. Conclusions: the results obtained will be useful for automating the risk management of retail chains. The practical value is that the obtained results of real data for the network have demonstrated the possibility of using the developed tool for automatic allocation of resources in the form of pareto-optimal portfolios in order to minimize risks.

STUDY OF PHASE VOLTAGE AND LOAD SYMMETRATION IN ACTIVE-ADAPTIVE DISTRIBUTION ELECTRIC NETWORKS

Networks of 0.4 kV are characterized by a large unbalance of loads in phases. Current unbalance leads to voltage unbalance and additional losses of electrical energy. As a result, the voltage at the consumer may not meet the quality standards of electrical energy. In addition, due to unbalance, the service life of electrical equipment is reduced. Since the effect of stress balancing significantly depends on the place of balancing loads on the line, the paper proposes to determine the places of balancing loads by solving a multicriteria optimization problem. The paper proposes an objective function that minimizes active power losses and contains the total index of active power losses and indices of voltage unbalance coefficients in the negative and zero sequence.
 
 The purpose of the study is to obtain an effective objective function for determining the places of balancing loads and voltages in the network, which ensures a minimum of active power losses and the values of the voltage unbalance factors within the required limits; conduct a study of balancing loads and voltages depending on the places of balancing.
 
 Materials and methods. In the work, methods for calculating electrical networks were used, taking into account voltage losses and active power. To study the places of balancing loads and voltages, the method of multicriteria optimization with restrictions was used. The study of the objective function was carried out on a mathematical model of a low voltage overhead line. All calculations were carried out in MATLAB.
 
 Research results. A review and analysis of modern tools and methods for balancing loads and voltages in low voltage networks has been carried out. As a result of the analysis, it was concluded that there is no algorithm for determining the places of load balancing in low-voltage networks that provide minimal active power losses and the values of the voltage unbalance factors within the required limits. The task of finding places for balancing loads and voltages is a multiobjective optimization problem with constraints. Therefore, an objective function was proposed that minimizes active power losses in the network and contains the total index of active power losses and indices of voltage unbalance coefficients for the reverse and zero sequence. To study the proposed objective function, a model overhead line of a 0.4 kV network with specified phase loads and voltages was used. For the model line, the calculation of active power losses and the values of the voltage unbalance coefficients in the initial mode before balancing was carried out. All calculations were carried out for each phase separately. At the first stage, the calculation of the sensitivity coefficients of active power losses and the sensitivity coefficients for the voltage unbalance coefficients was carried out. To study the balancing of loads, nodes were selected that have the maximum values of the sensitivity coefficients. It follows from the calculation results that the best effect from balancing is observed when balancing loads simultaneously in two nodes: in the node with the highest value of the total sensitivity factor of active power losses, and in the node with the maximum value of the phase sensitivity factor of active power losses. When balancing loads in only one of the nodes, the most optimal of the selected ones will be the node most remote from the TS. We also obtained weight coefficients that provide a minimum of the objective function.
 
 Conclusions. The proposed objective function is effective for determining the places of load and voltage balancing in low voltage networks. In this case, the best effect is observed when balancing loads in nodes that have the highest values of the sensitivity coefficients of total active power losses and by phases. The node most remote from the TP will be more optimal. When balancing loads in places determined using the proposed objective function, it is possible to reduce power losses and ensure the values of the unbalance coefficients in the nodes on the line less than the maximum allowable value.

О ПРИМЕНЕНИИ КРИТЕРИЕВ TEWI, LCCP И LCC ДЛЯ СРАВНЕНИЯ ЭНЕРГОПРЕОБРАЗУЮЩИХ ХОЛОДИЛЬНЫХ СИСТЕМ

The paper considers environmental metrics that assess the man-made impact of energy-converting refrigeration systems on the environment. The results of a comparative analysis of TEWI and LCCP obtained for a medium-temperature vapor-compression heat pump unit (VCHP) operating on refrigerants R1234ze, R1336mzz (E), R600a and R744 are presented. R1336mzz (E) has the worst environmental indicators, because the total emission of equivalent CO2 for the entire period of the life cycle exceeds the same indicator for R600a by 4.2 times. The LCCP results show that system performance and equipment manufacturing emissions are the dominant drivers of CO2 emissions over the life of the SHP unit. The results of comparing refrigerants based on TEWI and LCCP are directly proportional and depend on the amount of energy consumed by the VCHP, which is also reflected in the energy efficiency indicators of the system. It is advisable to take into account the TEWI, LCCP and LCC criteria when comparing and selecting energy-converting refrigeration systems using the multi-criteria optimization method, which will help the user get a more informative understanding of the VCHP.

Methods of vehicle selection in the multimodal passenger transportation system

The article presents the results of the analysis of the methods of justification and choice of vehicles in the organization of long-distance multimodal passenger transportation involving water and related modes of transport. The analysis of the factors determining the need to use a combined approach in the organization of passenger transportation is carried out. Analytical and mathematical methods of selecting modes of transport are considered, including methods of multi-criteria optimization in the problem of selecting vehicles in the combined passenger transport system. An algorithm for selecting vehicles in the multimodal passenger transportation system has been compiled, which takes into account all of the above stages. The calculation of quantitative and analysis of qualitative indicators of the choice of the mode of transport with the participation of water transport and specific vehicles is carried out on the example of the organization of the passenger line "Nizhny Novgorod – Kazan – Samara" using various schemes of combining modes of transport. The proposed approach and algorithm for the complex solution of the problem ensure the coordination of the economic interests of the interacting modes of transport and increase the attractiveness of long-distance multimodal communication for passengers

Renewable Energy Transition Task Solution for the Oil Countries Using Scenario-Driven Fuzzy Multiple-Criteria Decision-Making Models: The Case of Azerbaijan

The renewable energy transition of oil- and gas-producing countries has specific peculiarities due to the ambivalent position of these countries in the global energy market, both as producers and consumers of energy resources. This task becomes even more challenging when the share of oil and gas in the country’s GDP is very high. These circumstances pose serious challenges for long-term energy policy development and require compromising decisions to better align the existing and newly created energy policies of the country. The scale, scope, and pace of changes in the transition process must be well balanced, considering the increasing pressure of economic and environmental factors. The objective of this paper is to develop models that allow the selection of the most appropriate scenario for renewable energy transition in an oil- and gas-producing country. The distinguishing feature of the proposed model is that alternatives in the decision matrix are presented as scenarios, composed of a set of energy resources and the level of their use. Linguistic descriptions of the alternative scenarios are formalized in the form of fuzzy statements. For the problem solution, four different Multiple-Criteria Decision-Making (MCDM) methods were used: the fuzzy simple additive weighting (F-SAW) method, the distance-based fuzzy TOPSIS method (Technique of Order Preference Similarity to the Ideal Solution), the ratio-analysis-based fuzzy MOORA method (Multi-Objective Optimization Model Based on the Ratio Analysis), and the fuzzy multi-criteria optimization and compromise solution method VIKOR (Serbian: VIekriterijumsko Kompromisno Rangiranje). This approach is illustrated using the example of the energy sector of Azerbaijan. The recommended solution for the country involves increasing natural gas (NG) moderately, maintaining hydro, and increasing solar notably and wind moderately.

Мathematical model of the problem of optimizing logistics networks under conditions of interval determination of input data

Problem. In the conditions of rapid changes in demand and supply in transportation markets, there is a need for corresponding changes in logistics technologies and networks, which are carried out through their reengineering. Existing mathematical models for the optimization of logistics networks are designed for conditions with point-wise, clearly defined input data, which does not allow obtaining solutions resistant to changes in the external environment. This determined the relevance of the scientific and applied task of developing mathematical models of multi-criteria optimization problems of logistics networks for the conditions of interval submission of input data. Goal. The goal is to increase the efficiency of the logistics network optimization technology at the stage of re-engineering by developing a mathematical model of the multi-criteria optimization problem for the conditions of interval submission of input data. Methodology. According to the results of the decomposition of the problem of system optimization of logistics networks as the most complex defined task of their structural and topological optimization. When developing the model, the methodology of system design of territorially distributed objects, methods of multi-criteria optimization, theories of utility and decision-making were used. The apparatus of interval mathematics was used to compare solution options with vaguely specified input data. The results. The result are the formulated and completed formalization of the task of optimizing logistics networks as territorially distributed objects. The relationship for the objective function and constraints of the optimization task of topological structures of centralized three-level logistics networks is proposed. Originality. A mathematical model of the task of reengineering topological structures of centralized three-level logistics networks according to cost and efficiency indicators for interval defined input data and values of local criteria using comparison indices based on the Hukuhara difference has been developed. Practical value. The obtained results make it possible to increase the reliability of optimization results in the processes of design, development planning and reengineering of logistics networks, to obtain variants of the construction of their topological structures that are resistant to changes in external conditions.

Advantages of IMRT optimization with MCO compared to IMRT optimization without MCO in reducing small bowel high dose index for cervical cancer patients-individualized treatment options.

Traditional intensity-modulated radiation therapy (IMRT) planning for cervical cancer is time-consuming and require iterative repeated optimization. In this study, we focused on leveraging multi-criteria optimization (MCO) to reduce the impact of small bowel high-dose indices on other optimization targets, thereby providing a rapid approach to individualized IMRT for cervical cancer patients. Our research involved a cohort of 25 cervical cancer patients who underwent IMRT radiotherapy. The patient inclusion criteria were as follows: (I) histopathological confirmation of cervical cancer, (II) underwent IMRT radiation therapy, and (III) a prescribed dose of 180 cGy/28 fractions for the patient. All plans were replanned by an experienced dosimetrist without the MCO (W-IMRT). On the basis of the W-IMRT plan, the individualized IMRT (I-IMRT) plan was generated under the priority trade-off of reducing the D2cc (D2cc is the minimal dose to the 2 cm3 of the small bowel receiving the maximal dose) index of the small bowel using the MCO method, maintaining target coverage and protecting other organs at risk (OARs) as much as possible. Statistical analysis was performed using the Wilcoxon signature rank test. When the MCO method was applied to the IMRT plan, the high dose index decreased in the overlapping area between the small bowel and the planning treatment volume (PTV) (P<0.001, respectively). The D2cc index of the small bowel decreased to below 5,200 cGy in all I-IMRT plans. On the other hand, in PTV, the I-IMRT plan achieved a better homogeneity index (HI) compared to the W-IMRT plan. Significant dose reductions were also observed in the bladder (Dmean 144.8 cGy and V40 1.45%) (P<0.001, respectively), rectum (Dmean 43.9 cGy and V40 2.7%) (P<0.001, respectively) and bilateral femur heads (Dmean 150 cGy) (P<0.001, respectively). Dosimetric differences suggest that the I-IMRT plan using the MCO method provides better protection of other OARs and equivalently in PTV coverage, while lowering the high-dose index in the small bowel as much as possible for patients with cervical cancer, thus providing a rapid approach to achieving individualized IMRT for cervical cancer patients.

Optimization methods for multi-criteria decisions in pharmacy

Optimization methods for multi-criteria decisions in pharmacy&#x0D; In pharmaceutical technological research, the determination of the quantitative composition of granules is considered as a task of multi-criteria selection. Today, to solve this problem, the regression analysis and multi-criteria optimization methods are widely used; they are based on mathematical models obtained for the object under study.&#x0D; Aim. To identify a decision-making method in a multi-criteria space that is effective for use in pharmaceutical technology research with quantitative factors.&#x0D; Materials and methods. The study uses tools of the popular computer mathematics system Mathcad (MathSoft Ins., USA) to automate the solution of mathematical problems. To automatically search for the type and coefficients of regression equations, the MS Excel application was used, namely: the data analysis package (regression analysis). The MS Word processor was used to edit the code.&#x0D; Results. A variety of approaches to the formalization of the multi-criteria optimization task have been studied. The optimal quantitative content of excipients when developing the granule technology has been found using two different optimization criteria, which are formed according to different methodical approaches. The method proposed does not provide for the mandatory introduction of gradation of individual criteria or their weighting factors.&#x0D; Conclusions. As a result of the comparison of multi-criteria optimization methods, the effectiveness of the decision-making method in the multi-criteria space has been shown; it synthesizes a mathematical procedure related to the vector of criteria and is based on determining the ideal point and introducing the concept of a norm into the space of functionals; it has not been mathematically proven, but it is practically useful decision-making algorithm compared to the mathematical method of convolution of criteria. The optimization method proposed has advantages that are manifested in the possibility of using a relatively simple mathematical apparatus and simplified logic of obtaining a solution.

TRANSACTIVE LOCAL ELECTRICAL ENERGY SYSTEMS: FUNCTIONING FEATURES AND DEVELOPMENT PROSPECTS

Due to global concerns about climate change, the deployment of distributed energy resources and electrical and thermal energy storage systems has been accelerated to minimize CO2 emissions. In addition, the need for optimal energy management of these energy resources was emphasized in order to reduce the need for new energy resources. The concept of transactional energy and, accordingly, transactional systems was introduced for modern energy systems as a system of economic and control mechanisms that allow for dynamic balancing of supply and demand in the entire electrical infrastructure using cost as a key indicator. This ensures cost-effective integration of renewable energy sources and creates incentives for investment and innovative renewal of local energy systems, allowing for management of both supply and demand for electricity. The article discusses the architecture of transactional systems and its components. The main objective function of transactional systems is to minimize the total annual costs of the local system, which supports the continuity of energy supply. To estimate the current cost of electricity, it is necessary to have information on the distribution of investments invested in the project before the start of its implementation, between the periods of project implementation. Considered optimization criteria, the use of which depends on specific goals. It is important to use multi-criteria optimization and control methods to determine the structure of the system and the optimal distribution of energy obtained from different sources in order to maximize the efficiency of the entire system, while contributing to the maximum reduction of emissions to the environment, while minimizing the cost of energy production.

THE CURRENT STATE OF BLADE MACHINING WITH BLOCK-MODULAR TOOLS ON HEAVY-DUTY CNC MACHINES

The article analyzes the current state of the problem of blade machining, considers ways to improve the efficiency of the machining process on heavy unique machine tools, prefabricated tool systems, tool reliability, evaluates methods for ensuring satisfactory chip formation and their technological capabilities, considers methods of multicriteria optimization, identifies areas of scientific research, and formulates the purpose and objectives of the study. For the first time, the scientific principles of creating block-modular tooling systems for heavy machine tools were published, which include: principles of creating block-modular tooling systems based on qualimetric assessment of the states of the machining process, possible failures of the technological system, properties and criteria for their optimization, determination of the criteria weights; principles of designing block-modular tool elements taking into account the assessment of the stress-strain state and stiffness of the main components, creation of a mathematical model.

Intelligent decision-making support system for the commissioning of a small hydroelectric power plant in the Republic of Tyva

This paper investigates the cutting forces arising when using a single abrasive grain. Analytical studies were carried out using a model of a single abrasive grain in the form of a rod with a radiused apex acting on the workpiece material. The slip-line method (method of characteristics) was used to calculate the deformation intensity of a plastically edged workpiece material under the action of a single grain. Mathematical models were developed for the following factors: plastic deformation of the material, edging of the stagnated zone and its friction against the grain surface when moved upwards in the form of chippings, grain friction against the plastically deformed material, and the action of the dynamic component of plastic deformation. The significance of the dynamic component in the overall balance of forces related to plastic deformation was established by determining the ratio of dynamic stress on the break line and shear yield point. This dependence calculated for D16T and 30HGSA materials showed the feasibility of accounting for the dynamic component system based on a small hydropower station located in the Todzhinsky district of the Republic of Tyva. For an adequate assessment of the operational reliability of hydropower units, a logical and probabilistic method based on the kinetic theory of fault tree was used. The method allows the failures of the used equipment, as well as unplanned shutdowns of units due to a shortage of water resources in the Great Yenisey (low water, overdrying, and frozen frost), to be taken into account. The development of a generation system based on a small hydroelectric power plant for the settlements in the Todzhinsky district of the Republic of Tyva offers a load of up to 2,500 kW, which helps to reduce the cost of purchasing, delivering, and storing diesel fuel, while diesel generators can be used as backup power sources. 3 scenarios of structuring a small hydroelectric power plant were considered that involved various numbers and total capacity of hydrogenating units: 5x500 kW, 4x630 kW, and 3x800 kW. Therefore, by using the multi-criteria optimization method, the optimal structure of the generating system based on a small hydroelectric power plant having three hydroelectric units (each characterized by a capacity of 800 kW) was selected from the three proposed options, taking into account the reliability and uncertainty of the initial information.

A stochastic investment decision making method for distribution system resilience enhancement considering automation, hardening and distributed energy resources

Extreme weather events have always posed as a serious threat to the power system. In recent years the frequent occurrences of extreme events highlight the requirement for a resilient distribution system capable of maximizing load restoration under the most adverse situations. Because the requirement to reinforce the distribution system appears to be an expensive approach, it is crucial to make the proper investment decisions. In this regard, this article introduces a single-stage stochastic multi-criteria optimization method for maximizing network resilience over a series of investments while minimizing overall costs. This method conducts different categories of investments including the installation of sectionalizing switches, distributed energy resources, and hardening of overhead distribution lines. The optimization method is based on a genetic algorithm and can be used to address a large-scale network. Several numerical studies are tested on the IEEE 69-bus system to verify the effectiveness of the proposed method. The results of the investment decision-making method show the significance of combining planning and operational preparedness in distribution systems to respond to extreme weather events.