Multi-criteria Optimization Method Research Articles

Multiple-Criteria Decision-Making for Medical Rescue Operations during Mass Casualty Incidents

Mass casualty incident (MCI) is an unpredictable situation where a great number of people have been injured after an accident or sudden disease. Survival of the injured in the MCI depends on the efficiency of the directed emergency system (DES). The organization and management of medical assistance is of paramount importance. The shortest possible time to provide medical services to injured persons is crucial. The medical service in the case of the MCI primarily requires decisions on the priority of the order of treatment of the injured, the choice of medical transport and the location of specialized emergency treatment. As part of this paper, the effectiveness of the DES has been analyzed, and criteria used to improve rescue operations have been formulated. A formalized mathematical description of the medical rescue operations in MCIs has been proposed, and the optimization problem as the mixed integer linear programming (MILP) task was formulated. Optimization of an example case of rescue operations in MCIs has been presented. A computer simulator for optimal decision-making in medical rescue operations (CSMRO) has been developed for this purpose. The CSMRO implements various multi-criteria optimization methods to solve the formulated problem of rescue operations optimization. The results of computations made with the developed CSMRO simulator significantly shorten the time of decision-making in mass casualty incident handling.

Application of multiobjective optimization methods for solving of a ship design problem

In the present paper we demonstrate the application of single-objective and multi-objective optimization methods for solving the problem of ship design characteristics optimization. The impact analysis of local criteria on the values of design characteristics and elements of a ship has been carried out. The most frequently used methods of multicriteria optimization and their application to solving the problem of ship design characteristics substantiation, with taking into account the requirements to seakeeping and economic efficiency are considered. The multicriteria optimization results obtained by different methods are compared with the results of single-criteria optimization. Finally, numerical examples are implemented to demonstrate that an attempt to find a compromise solution often decrease the values of local criteria of optimality. It is established that the application of multi-criteria optimization methods for solving the ship design problems makes clear the role of each local optimality criteria and assess it influence on functional efficiency and design characteristics values.

CHOICE OF EXCAVATION METHOD OF THE ORE DEPOSITS

<p>The paper defines choice of the optimal excavation method for ore deposits, which are characterized by general irregularity due to their origin, occurrence and different content of the usable minerals. In such complex conditions, the choice of the excavation method is defined according to: the natural characteristics of the deposit and according to the techno - economic parameters of the comparison methods and the methods of multi-criteria optimization. </p>

МЕТОДЫ НЕЧЕТКОГО МНОГОКРИТЕРИАЛЬНОГО ГРУППОВОГО ПРИНЯТИЯ РЕШЕНИЙ ДЛЯ ЗАДАЧ ЭВАКУАЦИИ ПРИ ЧРЕЗВЫЧАЙНЫХ СИТУАЦИЯХ

The purpose of this article is to analyze the current state of research in the field of fuzzymulticriteria optimization methods, as well as the development of aggregation operators and algorithmsusing fuzzy multicriteria group decision-making using an intuitionistic attitude of linguisticpreferences. The most well-known fuzzy methods of multicriteria optimization are presented:ELECTRE, PROMETHEE, VIKOR, TOPSIS, AHP, ANP, MACBETH, DEMATEL, Shoke integraland DEA, their features, applications and the most cited articles are considered. Most real optimizationproblems may have conflicting goals. The method of fuzzy multi-purpose decision-makingFMODM is also presented for situations where there are inaccuracies and uncertainty in somegoals and variables on which they depend; methods of fuzzy multi-purpose linear programmingFMOLP, fuzzy multi-objective target programming FMOGP and fuzzy heuristic decision-makingmethods. The problem of fuzzy multicriteria group decision-making during evacuation with anintuitive relation of linguistic preferences is considered. It is noted that fuzzy logic methods areparticularly suitable for making evacuation decisions when there is little data, knowledge ofcause-and-effect relationships is inaccurate, and observations and criteria can be expressed inlinguistic qualitative terms. The main stages of group making the best decision among alternativesin a fuzzy environment are presented: combining expert assessments; obtaining a final assessmentfor each alternative represented by a linguistic variable; ranking alternatives; group making themost preferred decision. An approach to group decision-making with an intuitive preference relationshipbased on aggregation procedures is proposed. The group model of decision-making andthe concept of fuzzy group decision and linguistic variables used in predicting an emergency situationand planning evacuation are considered. It is noted that the well-known operators of orderedweighted averaging OWA, LOWA do not take into account the weights of experts. The Low operatoris defined, which allows taking into account the weight values of experts, as well as an approachto determining a fuzzy group solution of aFCS as a type 2 set. Algorithms for determininga fuzzy group multicriteria solution based on aFCS are presented

Dosimetric comparison of VMAT standard optimization (SO) and multi-criteria optimization (MCO) treatment plans with standard mode delivery (STD) or sliding window (SW) for head and neck cancer.

A new development on the RayStation treatment planning system (TPS) allows a plan to be planned by imposing a constraint on the leaf sequencing: all leaves move in the same direction before moving again in the opposite direction to create a succession of sliding windows (SWs). The study aims to investigate this new leaf sequencing, coupled with standard optimization (SO) and multi-criteria optimization (MCO) and to compare it with the standard sequencing (STD). Sixty plans were replanned for 10 head and neck cancer patients (two dose levels simultaneously SIB, 56 and 70Gy in 35 fractions). All plans were compared, and a Wilcoxon signed-rank test was performed. Pre-processing QA and metrics of multileaf collimator (MLC) complexity were studied. All methodologies met the dose requirements for the planning target volumes (PTVs) and organs at risk (OARs). SO demonstrates significantly best results for homogeneity index (HI), conformity index (CI), and target coverage (TC). SO-SW gives best results for PTVs (D98% and D2% ) but the differences between techniques are less than 1%. Only the D2%,PTV-56Gy is higher with both MCO methods. MCO-STD offer the best sparing OARs (parotids, spinal cord, larynx, oral cavity). The gamma passing rates (GPRs) with 3%/3mm criteria between the measured and calculated dose distributions are higher than 95%, slightly lowest with SW. The number of monitor units (MUs) and MLC metrics are higher in SW show a higher modulation. All plans are feasible for the treatment. A clear advantage of SO-SW is that the treatment plan is more straightforward to planning by the user due to the more advanced modulation. MCO stands out for its ease of use and will allow a less experienced user to offer a better plan than in SO. In addition, MCO-STD will reduce the dose to the OARs while maintaining good TC.

Machine-Learning-Based Consumption Estimation of Prestressed Steel for Prestressed Concrete Bridge Construction

Accurate prediction of the prestressed steel amount is essential for a concrete-road bridge’s successful design, construction, and long-term performance. Predicting the amount of steel required can help optimize the design and construction process, and also help project managers and engineers estimate the overall cost of the project more accurately. The prediction model was developed using data from 74 constructed bridges along Serbia’s Corridor X. The study examined operationally applicable models that do not require indepth modeling expertise to be used in practice. Neural networks (NN) models based on regression trees (RT) and genetic programming (GP) models were analyzed. In this work, for the first time, the method of multicriteria compromise ranking was applied to find the optimal model for the prediction of prestressed steel in prestressed concrete bridges. The optival model based on GP was determined using the VIKOR method of multicriteria optimization; the accuracy of which is expressed through the MAPE criterion is 9.16%. A significant average share of 46.11% of the costs related to steelworks, in relation to the total costs, indicates that the model developed in the paper can also be used for the implicit estimation of construction costs.

Моделювання оптимального інвестиційного портфеля орієнтованого на мінімізацію ризику

Abstract. Introduction. Portfolio optimization modelling is a study aimed at determining the best way to allocate an investor's funds between securities of different companies. The study uses a number of methods and approaches, such as: multicriteria optimization methods - optimization of criteria for minimum and maximum, modeling of the optimal stock portfolio with minimal risk, to determine the best way to allocate funds that will help investors achieve maximum return while minimizing risk. Purpose. There are a lot of publicly traded companies in the modern American stock market. Having chosen the companies that may grow in the future, the problem of allocating your funds among them remains relevant. Building an optimal portfolio of securities using various economic and mathematical methods solves the problem of allocating financial resources, focusing on the desired future profit and the level of risk exposure. Results. The model for this study was built using one of the methods of multi-criteria optimization - criteria convolution, taking into account portfolio diversification and the specified constraints. The optimization is based on the "Modern Portfolio Theory" of the prominent scientist Harry Markowitz. Conclusions. As a result, we built an optimal and diversified portfolio of shares, in which each company on the list represents at least 1%. All constraints have been met and the main conditions have been fulfilled - the portfolio minimizes risk and maximizes profit. With a minimum risk of 5.39%, we expect a return of 1.75%. Such results can be obtained if we use a convolution of the criteria where the preference is given to minimizing risk - 0.7. The largest contributors to the portfolio were the following companies: T-Mobile Us Inc., McKesson Corporation, The Kroger Co., Microsoft Corporation, and Apple Inc. These companies account for a significant portion of the portfolio - 65%. Given the focus on portfolio diversification and the ratio of risk to potential return, we can say that the portfolio is efficient and can be used in practice.

Optimizing composite floors for sustainability and efficiency: Cross laminated timber, concrete types, and ductile notch connectors with enhanced shape

Timber-concrete composite (TCC) structures allow designing efficient building floors in terms of lightness, slenderness, and acoustic insulation. The late development of ductile notch connectors has further advanced TCC structures. This work aims to further optimize the shape of ductile notch connections and to optimally design TCC floors with minimum embodied carbon, floor thickness, self-weight and cost.Firstly, an experimental campaign was carried out to characterize the shear behavior of ductile notch connectors with different shapes, which varied from rectangular to trapezoidal to avoid the use of screws, and concrete types, which varied from normal concrete to ultra-high performance fiber reinforced concrete. For the sake of comparison, a glued connection was also considered. Then, a multi-criteria optimization method was performed to optimally design TCC floor with the developed notch connectors and concrete types. The latest design recommendations for TCC floors developed in Canada were considered. A Non-Linear Finite Element Analysis (NLFEA) was carried out for validation. The presented results push the current design limits in terms of embodied carbon and volume of construction materials towards climate-positive floors.

Statistical and Water Management Assessment of the Impact of Climate Change in the Reservoir Basin of the Volga–Kama Cascade on the Environmental Safety of the Lower Volga Ecosystem

When managing water resources in order to provide water to consumers, a number of consequences arise related to the violation of the hydrological regime due to the regulation of flow by reservoirs. The second factor is possible climate change. These changes can negatively (or positively) affect the functioning of aquatic ecosystems. To reduce the impact on the environment, it is necessary to determine the nature and indicators of changes in the hydrological regime, calculate quantitative estimates of these indicators and ranges of acceptable values, and develop release rules that ensure compliance with these ranges with a given probability. To manage the water resources of the Volga and Kama Rivers, the main ecological task is to flood the floodplain meadows, to maintain the conditions of natural reproduction of fish on the Lower Volga, including the Volga River delta and the Volga–Akhtuba floodplain. In addition, it is necessary to meet with sufficient reliability the requirements of energy in the summer–autumn and winter low-water periods and water transport during the navigation period. The task of optimal management is to find such solutions in years of different water content that ensure the well-being of the main water users with a given probability and do not disturb the Lower Volga ecosystem. This article presents the research of the water resources state of the water resource system of the Volga and Kama river basins. A statistical analysis of the hydrological series of the observed inflow for 1916–2020 was performed, and the inflow change point (1979) was found by the Bayesian method of estimation. A statistically significant difference between the average inflow values of two series (1916–1978, 1979–2020) was proved using a two-sample Student’s test. The seasonal parameters of the reliability curves were calculated based on the three-parameter Kritsky and Menkel distribution. For these two series, water resource optimization calculations (using Excel Solver) were performed, and the reliability of fulfilling the requirements of water users was determined; for the series 1916–1978, an alternative solution was found in favor of fisheries, and an analysis of the results was also performed. The methodology used in the research allows finding trade-off solutions in the favor of different water users (ecology, agriculture and fisheries, water supply, hydropower, navigation, etc.) and is based on the use of multi-criteria optimization methods and the trade-offs theory. As a result of the research, new knowledge was obtained about the hydrological situation in the basin of the Volga–Kama reservoir cascade in connection with climate change.

A comparative analysis of DOACs vs warfarin for venous thromboembolism treatment in renal insufficiency

Aim: Annually, millions of people die from kidney diseases making it a serious public health concern. Patients with renal insufficiency have hemostatic defects that enhance their risk of thrombosis and bleeding. Evaluating the advantages and hazards of anticoagulant thromboprophylaxis is challenging. Material and Methods: By using the fuzzy preference ranking organization method for enrichment evaluation (fuzzy PROMETHEE) and fuzzy multi-criteria optimization and compromise solution (fuzzy VIKOR), which are analytical multi-criteria decision-making (MCDM) techniques, this study aims to analyze diverse types of anticoagulants; specifically, Vitamin K-Antagonist (warfarin) and direct oral anticoagulants namely; Dabigatran, Rivaroxaban, Apixaban, and Edoxaban, by considering various criteria. Results: Direct oral anticoagulants outperformed warfarin in terms of safety and effectiveness. Among all the analyzed anticoagulants, Apixaban was found to be the best-ranked anticoagulant with both fuzzy PROMETHEE and fuzzy VIKOR, with a net flow of 0.0064 and the lowest Qj value of 0.0000, respectively, compared with other alternatives depending on the selected criteria while warfarin was found to be the least ranked anticoagulant with a net flow of -0.0043 and the highest number of Qj being 1, respectively. Conclusion: The MCDM techniques used were effective, highly accurate, and sensitive in the comparison of anticoagulant therapy for venous thrombosis in renal insufficiency based on the chosen criteria. The proper use of a safe and effective anticoagulant will boost better performance not only in patients’ survival and well-being but also in the health care center.

Optimising Characteristics of an Intelligent Transport System Using a Real-Coded Genetic Algorithm Based on Adaptive Mutation

A novel real-coded genetic algorithm (FCGA-AM) that uses the proposed adaptive mutation (AM) operator is presented. The algorithm is designed to optimise the characteristics of the developed intelligent transportation system. The performance of the proposed genetic algorithm was evaluated in comparison with other methods of multicriteria heuristic optimization with the use of various test instances and well-known quality metrics for Pareto frontiers. At the next stage, the FCGA-AM was applied to find the best road safety trade-offs involving unmanned ground vehicles (UAVs) interacting with conventional ground vehicles (UTVs), pedestrians and other agents

Application of Multi-Criteria Optimization Methods in the Calibration Process of Digital Measuring Instruments

The article describes the use of multi-criteria optimization methods during the calibration of digital multimeters. Currently, calibration is based on a single measurement of a specific value. The aim of this research was to confirm the possibility of using a series of measurements in order to reduce the measurement uncertainty without significantly extending the calibration time. The automatic measurement loading laboratory stand used during the conducted experiments was essential to obtain results that allowed confirming the thesis. This article presents the applied optimization methods and the results of the calibration of sample digital multimeters obtained thanks to them. As a result of the research, it was found that the use of a series of measurements increased the accuracy of the calibration, reduced the measurement uncertainty, and shortened the calibration time compared to traditional methods.

Methodology for Optimizing Factors Affecting Road Accidents in Poland

With the rapid increase in the number of vehicles on the road, traffic accidents have become a rapidly growing threat, causing the loss of human life and economic assets. The reason for this is the rapid growth of the human population and the development of motorization. The main challenge in predicting and analyzing traffic accident data is the small size of the dataset that can be used for analysis in this regard. While traffic accidents cause, globally, millions of deaths and injuries each year, their density in time and space is low. The purpose of this article is to present a methodology for determining the role of factors influencing road accidents in Poland. For this purpose, multi-criteria optimization methods were used. The results obtained allow us to conclude that the proposed solution can be used to search for the best solution for the selection of factors affecting traffic accidents. Furthermore, based on the study, it can be concluded that the factors primarily influencing traffic accidents are weather conditions (fog, smoke, rainfall, snowfall, hail, or cloud cover), province (Lower Silesian, Lubelskie, Lodzkie, Malopolskie, Mazovian, Opolskie, Podkarpackie, Pomeranian, Silesian, Warmian-Masurian, and Greater Poland), and type of road (with two one-way carriageways; two-way, single carriageway road). Noteworthy is the fact that all days of the week also affect the number of vehicle accidents, although most of them occur on Fridays.

Development of an Algorithm for Multicriteria Optimization of Deep Learning Neural Networks

Nowadays, machine learning methods are actively used to process big data. A promising direction is neural networks, in which structure optimization occurs on the principles of self-configuration. Genetic algorithms are applied to solve this nontrivial problem. Most multicriteria evolutionary algorithms use a procedure known as non-dominant sorting to rank decisions. However, the efficiency of procedures for adding points and updating rank values in non-dominated sorting (incremental non-dominated sorting) remains low. In this regard, this research improves the performance of these algorithms, including the condition of an asynchronous calculation of the fitness of individuals. The relevance of the research is determined by the fact that although many scholars and specialists have studied the self-tuning of neural networks, they have not yet proposed a comprehensive solution to this problem. In particular, algorithms for efficient non-dominated sorting under conditions of incremental and asynchronous updates when using evolutionary methods of multicriteria optimization have not been fully developed to date. To achieve this goal, a hybrid co-evolutionary algorithm was developed that significantly outperforms all algorithms included in it, including error-back propagation and genetic algorithms that operate separately. The novelty of the obtained results lies in the fact that the developed algorithms have minimal asymptotic complexity. The practical value of the developed algorithms is associated with the fact that they make it possible to solve applied problems of increased complexity in a practically acceptable time. Doi: 10.28991/HIJ-2023-04-01-011 Full Text: PDF

Maximizing Energy Performance of University Campus Buildings through BIM Software and Multicriteria Optimization Methods

University buildings have high energy requirements due to their size, numerous users, and activities, which considerably contribute to environmental contamination. Implementing energy-saving solutions in these structures has a favorable influence on the economics and the conservation of energy resources. A higher education building’s energy behavior can be simulated using software to identify the optimal strategies that result in energy savings. In this research, Autodesk Revit, Autodesk Insight, and Green Building Studio are among the programs utilized to examine the energy efficiency of the university building in four European cities. Following the development of several energy-saving scenarios for the building, the offered solutions are evaluated based on their annual energy consumption, energy costs, and CO2 emissions. Finally, multicriteria analysis techniques such as the AHP and PROMETHEE are applied to choose the best scenario for each instance. The study’s findings indicate that the ASHRAE Terminal Package Heat Pump scenario performed well in all of the cities examined, reducing yearly energy usage by 43.75% in Wien and annual energy costs by 47.31% in Mallorca. In comparison, the scenario utilizing a high-efficiency VAV system with a gas boiler and chiller came in last in all situations, resulting in a decrease of 12.67% in Mallorca’s annual energy usage and a reduction of 17.57% in Palermo’s annual energy expenses.

A comparative assessment of multicriteria parametric optimization methods for plasma arc cutting processes

Plasma arc cutting (PAC) has evolved as an efficient process to cut complex profiles on many hard-to-machine engineering materials due to its many advantages, like higher dimensional accuracy, higher productivity, and the capability to cut thick materials. Optimization of this process is challenging due to existence of many input parameters, complex cutting mechanism, and interactions of the process parameters with the responses. In this paper, the applications of four newly developed multicriteria decision-making (MCDM) tools, i.e., Proximity Indexed Value (PIV), Evaluation by an Area-based Method of Ranking (EAMR), Pareto-Edgeworth Grierson (PEG), and Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval (RAFSI) are presented for optimization of two PAC processes. To study the effects of criteria (response) weights on the optimization performance of the adopted MCDM techniques, two objective criteria weighting techniques, i.e., Criteria Importance Through Intercriteria Correlation (CRITIC) and Method based on the Removal Effects of Criteria (MEREC) are considered. All four MCDM techniques identify similar optimal parametric combinations at two different criteria weighting scenarios. The calculated Gini indexes also validate the superiority of the derived optimal parametric intermixes over the other experimental trials and similarity of the ranking performance of all four MCDM techniques.

A methodical approach to the multi-criteria selection in the pharmaceutical technological research with quantitative factors

Aim. To analyze the existing methods for solving multi-criteria optimization problems with quantitative factors and consider the expediency of their application in the pharmaceutical technological research. Materials and methods. The theoretical and empirical methods, as well as scientific data on multi-criteria optimization methods were used in the research. Results and discussion. It has been found that when conducting the research with quantitative factors the statistical methods for processing the results of experiments are used. It has been determined that the regression analysis allows us to present the dynamics of changes in the pharmacopoeial characteristics studied from variable quantitative factors in a compact form. It has been found that regression equations enable the researcher to effectively search for optimal conditions for conducting technological operations and are local criteria for finding the optimal solution. It has been proven that the need to optimize several criteria simultaneously when developing the technology of a medicinal product allows considering the tasks of multi-criteria selection in the pharmaceutical research as a special class of decision-making problems that are on the verge between the research of operations for well-structured quantitative situations and decision-making tasks, which methods of solving differ. Conclusions. To determine the optimal solution in the course of the pharmaco-technological development, a method for finding an ideal point has been proposed as a synthesis of mathematical calculations and decision-making procedures by a researcher. The search is conducted in the range of acceptable values of variables and determines their totality, which is able to provide a set of values of pharmaco-technological criteria that is closest to the optimal option determined by the researcher. This approach involves preliminary solution of single-criterion optimization problems for each individual criterion and reduction of all to a mathematical form that determines the minimum deviation of the objective functions obtained from the optimal values.

A Methodology for Multi-criteria Assessment of Chiller Plants for Building Setup Utilising Waste Heat and Solar Energy

Incorporating a central chilled water hub within an eco-industrial park may boost cost-cutting and carbon reductions. Yet, there are various ways to power it, each with its own set of advantages and disadvantages in respect of cost, environmental impact, and technological feasibility. Consequently, it might be challenging to negotiate a settlement with other members in an eco-industrial park because of their conflicting interests. A multi-criteria optimization method is used in this study to compare several centralized chiller systems that are powered by varying compositions of energy forms, to reduce total yearly expenditures for the whole complete building setup. An electric-driven chiller, multi-effect absorption chillers with several effects, and adsorption chillers are installed in the centrally located chilled water system. These components were chosen so that the system could use a wide range of fuels, such as electricity, fossil fuels, chillers, and even solar energy. Afterwards, the TOPSIS is employed to do a multiple criterion ranking on all plans, relying not only on the interests of the building but also on the priorities of individual chiller plants. The conceptual approach assures that cost reduction and user comfort are considered throughout the development of a chilled water system for the building setup. Among the nine criterions selected for the study, The weightage calculated were as follows: Actual capacity- 18%, Total Input power-13%, Speed of Compressor- 5%, EER- 13%, Running current -6%, Max Starting current-6%, Flow rate- 6%, Input power- 19% and Operating Weight- 14%. While ranking chillers AC Screw 355 TR VFD achieved highest performance score of 0.54 followed by AC Screw 355 TR STAR-DELTA with a performance score of 0.51. The novel study will aid the building owners in selecting the best design for chillers while maintaining a sustainable aspect in chillers which is important in building to attain green structure model.

Retracted: Optimization of Zero-Energy Buildings Based on Multicriteria Optimization Method

Retracted: Optimization of Zero-Energy Buildings Based on Multicriteria Optimization Method

Сравнительный анализ методов решений оптимизационных задач для сельскохозяйственного машиностроения

To design intelligent transport and technical means, it is necessary to improve the methodological provisions and software for multi-criteria optimization of the functional properties of innovative mobile energy means. The right choice of optimization methods is necessary to design a reliable mathematical model. A comparative analysis of methods for optimizing problem solving for agricultural engineering showed the applicability of single-criterion methods in optimizing simple design parameters of single-purpose problems (development of parts, technical and technological characteristics of individual objects). Multicriteria optimization methods are applicable to solving problems with the defi nition of several objective functions with a large number of functional and criterion constraints, as well as variable parameters, where each parameter is not inferior in importance and relevance to each other (agricultural enterprise management, design of mobile power vehicles, combines and other agricultural machines). Vector optimization methods are applicable for solving a multicriteria optimization problem with a set of possible (permissible) solutions (designing elements of units, machine units and equipment for agricultural production). The authors have analyzed the existing software tools for solving optimization problems. They have found it necessary to develop software tools taking into account simultaneously up to 20 criterial and functional constraints, up to 50 variable parameters and more than three equally important objective functions, where each parameter has no precedence over the others.