Parallel Solution Research Articles

New Solution to Euler’s Equations for Asymmetric Bodies: Applications to Spacecraft Reorientation

This work derives the kinematic and dynamic solution to Euler’s equations of motion for an asymmetric rigid body subject to a torque aligned parallel or antiparallel to the instantaneous angular momentum vector. These are the first complete solutions to Euler’s equations for an asymmetric rigid body subject to nonaxial torques. The antiparallel solution is shown to be the optimal trajectory for spacecraft detumbling subject to a bound on the Euclidean norm of the applied torque. Comparisons to a numerically integrated optimal control law validate the solution for highly asymmetric spacecraft and long maneuver times. Combining the parallel and antiparallel torque solutions allows for the analytical expression of a rest-to-rest reorientation maneuver for any asymmetric spacecraft. This maneuver is completely parameterized by a single body frame angular momentum vector, and is thus termed a momentum-axis maneuver. Comprehensive trade studies indicate that the momentum-axis maneuver is superior in terms of maneuver time to time-optimal eigenaxis maneuvers for large-angle rotations, and generally within of numerically computed true optimum solutions. As these solutions are both analytic and computationally cheaper than either the eigenaxis or true optimum solutions, this approach could have widespread applications for spacecraft attitude control.

Valorization of Dairy By-Products: Efficiency of Energy Production from Biogas Obtained in Anaerobic Digestion of Ultrafiltration Permeates

This study aimed at evaluating the methane potential of two ultrafiltration (UFP) and two diafiltration (DFP) permeates generated during milk protein concentration. The permeates were characterized by a different chemical oxygen demand (COD) ranging from 7610 mg O2/L to 57,020 mg O2/L. The CH4 production efficiency was recorded for 20 days and ranged from 149 to 181 NL/kg CODadded. Moreover, the possibilities of the use of UFP/DFP to produce electricity and heat with a combined heat and power (CHP) unit was analyzed to underline the impact of the implementation of anaerobic digestion on the electric and thermal energy requirements of a dairy plant. It was concluded that the application of anaerobic digestion to UFP and DFP treatments generates the energy required to cover all the large-scale dairy plant energy demands and produce extra income. The amount of permeates generated annually in the analyzed dairy plant will enable the production of approx. 22,699 MWh of electricity and 85,516 GJ of heat. This would require a biogas plant with a 3 MW yield. Additionally, the lactose production from UFP/DFP was considered as an alternative or parallel solution for its management. The study confirmed that the biogas and lactose production from UFP/DFP enables plant owners to adjust a plant’s management towards one of these two solutions.

Parallel Weighted Random Sampling

Data structures for efficient sampling from a set of weighted items are an important building block of many applications. However, few parallel solutions are known. We close many of these gaps. We give efficient, fast, and practicable parallel and distributed algorithms for building data structures that support sampling single items (alias tables, compressed data structures). This also yields a simplified and more space-efficient sequential algorithm for alias table construction. Our approaches to sampling k out of n items with/without replacement and to subset (Poisson) sampling are output-sensitive , i.e., the sampling algorithms use work linear in the number of different samples. This is also interesting in the sequential case. Weighted random permutation can be done by sorting appropriate random deviates. We show that this is possible with linear work. Finally, we give a communication-efficient, highly scalable approach to (weighted and unweighted) reservoir sampling. This algorithm is based on a fully distributed model of streaming algorithms that might be of independent interest. Experiments for alias tables and sampling with replacement show near linear speedups using up to 158 threads of shared-memory machines. An experimental evaluation of distributed weighted reservoir sampling on up to 5,120 cores also shows good speedups.

The complexation of U(IV) ion with N, N, N′, N′-Tetraalkyl-Diglycolamide in aqueous solutions and extraction systems of varying anions

By comparing the absorption spectra of the two 1:3 species formed in 1 M HCl, 1 M HNO 3 and the reflectance spectrum of UL 3 ·4(ClO 4 ) (L = N, N, N′, N′-tetramethyl-diglycolamide) with the spectra of the extracted complexes of U(IV) with L′(L′ = N, N′-dimethyl-N, N′-dioctyl-diglycolamide), the participation of anions in the first coordination sphere is discovered in the extracted complexes of U(IV) with L′ for the first time in solvent extraction using tetraalkyldiglycoamides as extractants. • Three complex species of U(IV) with TMDGA are identified respectively in 1 M HNO 3 and 1 M HCl solution. • Single crystals of U(TMDGA) 3 ·4ClO 4 are grown and its structure is determined. • The participation of counter anions in the first coordination sphere of U(IV)in the extracted complexes with DMDODGA and in the complexes with TMDGA in HCl and HNO 3 media was confirmed. The complexation of U(IV) with N, N, N′, N′-tetramethyl-diglycolamide (TMDGA, L) has been investigated in 1 M HCl and 1 M HNO 3 solutions and in a solid compound UL 3 ·4(ClO 4 ) formed in aqueous solutions in parallel with that in the extraction system using N, N′-dimethyl-N, N′-dioctyl-diglycolamide (DMDODGA, L′) as extractant. Three species of U(IV):L complexes being 1:1, 1:2, and 1:3 (denoted as UL 4+ , UL 2 4+ and UL 3 4+ ) are identified spectroscopically in each of the two different aqueous media, 1 M HCl and 1 M HNO 3 . The different absorption spectra of the corresponding complexes indicate that the complexes formed in 1 M HCl and 1 M HNO 3 are not the same, suggesting that the anions Cl - and NO 3 – are involved in the complexes. By comparing the absorption spectra of the two 1:3 species formed in 1 M HCl, 1 M HNO 3 and the reflectance spectrum of UL 3 ·4(ClO 4 ) with the spectra of the extracted complexes of U(IV) with L′, the participation of anions in the first coordination sphere is discovered in the extracted complexes of U(IV) with L′ for the first time in solvent extraction using tetraalkyldiglycoamides as extractants.

Optimization of orderly charging strategy of electric vehicle based on improved alternating direction method of multipliers

When it comes to solving the optimization problem of wind power and large-scale electric vehicle (EV) synergistic access to the power grid, issues like the difficulty of accurately predicting wind power, the massive amount of information communication, the difficulty of handling EV constraints, and the privacy leakage of EV owners are critical. A distributed framework based on power grids, EV load aggregates, and single EV is established in this paper. Based on this framework, an EV rolling real-time optimization model considering wind power forecast errors and EV forecast information has been established. An improved alternating direction multiplier approach is utilized to solve the model, and a small amount of information is transmitted between the two agents in each iteration to achieve the parallel solution of each agent's optimization goals. Without requiring global coordination, the proposed architecture can achieve the goal of synchronous iteration. Finally, an example of a regional power grid is used, with EVs divided into three regions. The improved ADMM algorithm now has seven multipliers, and the problem is solved, with the load variation, wind power consumption, and EV before and after optimization compared. To evaluate the effectiveness and convergence of the improved ADMM algorithm, as well as the impact of prediction information, electricity power sales price, and vehicle owner preference coefficient on dispatching outcomes, the operator's operational cost and the EV owner's charging satisfaction are examined. The example's simulation results show that the developed model achieves the goal of cutting peaks and filling valleys to absorb wind power, reducing operating costs and improving EV owner satisfaction.

Adaptive Decision Method in C3I System.

As an important system in the national defense and military information construction, the command, control, communication, and intelligence (C3I) system urgently needs to establish an adaptive process to deal with the dynamic operating environment and changeable task requirements to ensure the long-term effective and stable operation of the system. As an important part of this process, the adaptive decision method should have the ability of online trade-off decision. Therefore, this paper presents an adaptive decision method based on parallel computing and optimization theory. This method combines operational requirements and commander preference to achieve the parallel adaptive decision solution. The experimental results show that the presented decision method can generate online trade-off strategies to deal with typical command and control scenarios of damage replacement in a simulated environment, effectively guide the system to carry out adjustment behavior, and achieve the goal of dynamic response to environmental changes and task changes.

Four-splitting based coarse-grained multicomputer parallel algorithm for the optimal binary search tree problem

ABSTRACT This paper presents a parallel solution based on the coarse-grained multicomputer (CGM) model using the four-splitting technique to solve the optimal binary search tree problem. The well-known sequential algorithm of Knuth solves this problem in time and space, where n is the number of keys used to build the optimal binary search tree. To parallelise this algorithm on the CGM model, the irregular partitioning technique, consisting in subdividing the dependency graph into subgraphs (or blocks) of variable size, has been proposed to tackle the trade-off of minimising the number of communication rounds and balancing the load of processors. This technique, however, induces a high latency time of processors (which accounts for most of the global communication time) because varying the blocks' sizes does not enable them to start evaluating some blocks as soon as the data they need are available. The four-splitting technique proposed in this paper solves this shortcoming by evaluating a block as a sequence of computation and communication steps of four subblocks. This CGM-based parallel solution requires execution time with communication rounds, where p is the number of processors and k is the number of times the size of blocks is subdivided. An experimental study conducted to evaluate the performance of this CGM-based parallel solution showed that compared to the solution based on the irregular partitioning technique where the speedup factor is up to ×10.39 on 128 processors with 40,960 keys when k = 2, the speedup factor of this solution is up to ×13.12 and rises up to ×14.93 when k = 5.

ParGeMSLR: A parallel multilevel Schur complement low-rank preconditioning and solution package for general sparse matrices

This paper discusses parGeMSLR, a C++/MPI software library for the solution of sparse systems of linear algebraic equations via preconditioned Krylov subspace methods in distributed-memory computing environments. The preconditioner implemented in parGeMSLR is based on algebraic domain decomposition and partitions the symmetrized adjacency graph recursively into several non-overlapping partitions via a p-way vertex separator, where p is an integer multiple of the total number of MPI processes. From a numerical perspective, parGeMSLR builds a Schur complement approximate inverse preconditioner as the sum between the matrix inverse of the interface coupling matrix and a low-rank correction term. To reduce the cost associated with the computation of the approximate inverse matrices, parGeMSLR exploits a multilevel partitioning of the algebraic domain. The parGeMSLR library is implemented on top of the Message Passing Interface and can solve both real and complex linear systems. Furthermore, parGeMSLR can take advantage of hybrid computing environments with in-node access to one or more Graphics Processing Units. Finally, the parallel efficiency (weak and strong scaling) of parGeMSLR is demonstrated on a few model problems arising from discretizations of 3D Partial Differential Equations.

Parallel solution of optimal control problems using the graphics processing unit

AbstractThis paper presents an indirect method for solving optimal control problems (OCPs) using graphics processing unit (GPU). The OCPs considered here include control variable inequality constraints (CVICs), state variable inequality constraints (SVICs), and parameters. The necessary conditions of the minimum for the OCPs are written as a boundary value problem with index‐1 differential algebraic equations (BVP‐DAEs). The complementarity conditions associated with those inequality constraints are approximated using Kanzow's smoothed Fisher‐Burmeister formula. The numerical solution for solving the BVP‐DAEs is based on the multiple shooting technique and the DAEs are solved using a single step linearly implicit Runge–Kutta (Rosenbrock–Wanner, ROW) method. A Newton's continuation method is performed to solve the BVP‐DAEs system and the descent direction is found by solving a sparse bordered almost block diagonal (BABD) linear system with a structured orthogonal factorization algorithm. Parallel computing techniques are used to accelerate the code which is implemented using Python and CUDA on GPU. Numerical examples are presented to illustrate the efficiency of the code. The GPU based parallel implementation is shown to be significantly faster than the implementation using central processing unit (CPU) alone.

Parallel Beam Search for Combinatorial Optimization (Extended Abstract)

Inspired by the recent success of parallelized exact methods to solve difficult scheduling problems, we present preliminary results of a general parallel beam search framework for combinatorial optimization problems. Beam search is a constructive metaheuristic traversing a search tree layer by layer while keeping in each layer a bounded number of promising nodes to consider many partial solutions in parallel. We propose a variant which is suitable for intra-node parallelization by multithreading with data parallelism. For sufficiently large problem instances and beam widths our work-in-progress implementation in the JIT-compiled Julia language admits promising speed-ups over 30x on 32 cores with uniform memory access for the Permutation Flow Shop Scheduling (PFSP) problem with flowtime objective.

Cloud-edge collaborative distributed optimal dispatching strategy for an electric-gas integrated energy system considering carbon emission reductions

To reduce carbon emissions and improve the energy efficiency of energy systems, integrated energy systems (IESs) have been promoted in recent years. However, the data of different energy networks cannot be fully shared. The data privacyprotection is attracting more attention in demand side. It is difficult for centralized dispatching strategies, which must obtain all the data of energy systems during optimization, to be applied. To solve these issues, a cloud-edge collaborative distributed optimal dispatching strategy for electric-gas IESs is proposed in this paper. The centralized IES scheduling problem is reasonably divided into multiple subproblems. Considering information barrier, the cloud computing centers are separately set in different energy networks to solve energy flow optimization subproblems. Considering prosumer privacy protection, edge computing units are separately set in energy hubs to deal with cost and carbon emissions minimization of regional integrated energy systems (RIESs). Based on the proximal Jacobian alternating direction method of multipliers, the common optimization variables interactive iteration and parallel solution of multiple dispatching models are developed. The simulation results show that the proposed distributed optimization method can achieve the same accuracy as the centralized optimization method and improve problem-solvingefficiency in general.

Parallel computational tree logic model‐checking on pushdown systems

SummaryModel checking and static analysis have been well studied for program verification. Because of the ability to describe the stack, the pushdown system (PDS) has become a perfect model that is able to accurately model procedure calls and mimic the program's stack. Thus, it is not only a good model for sequential programs but for malware detection as well. However, with the increase of the complexity of programs, the size of models becomes huge as well. Thus, the model‐checking problem is expensive to solve. The computational tree logic (CTL) is a widely used logic and its model checking problem of PDSs can be reduced to the emptiness analysis of an alternating Büchi pushdown system (ABPDS) by determining whether there is an accepting run. When the size of a PDS is huge, the computations can be time‐consuming. To overcome this limitation, we propose a parallel solution. We propose a parallel framework based on the Compute Unified Device Architecture and the corresponding parallel algorithms to solve the emptiness problem of ABPDSs. Moreover, in order to effectively utilize the graphics processing unit, we design a new data structure of variables and an algorithm of management of thread scheduling for the parallel model. We implement our algorithms in a tool and compare our tool to a CTL model checker for PDS as a benchmark. The comparison results indicate an encouraging performance speedup.

Globalization of Nonlinear FETI-DP Domain Decomposition Methods Using an SQP Approach

The globalization of Nonlinear FETI-DP (Dual Primal Finite Element Tearing and Interconnecting) methods is considered using a Sequential Quadratic Programming (SQP) approach. Nonlinear FETI-DP methods are parallel iterative solution methods for nonlinear finite element problems, based on divide and conquer, using Lagrange multipliers. In these methods, nonlinear elimination is an important ingredient to increase the convergence radius of Newton’s method. We prove standard globalization results for SQP-based globalization of Nonlinear FETI-DP, first for the case that the elimination set is empty. We then show how to combine nonlinear elimination and SQP-based globalization. The globalization preserves the block structure of the FETI-DP operator, which is the basis of the computational parallelism.Supporting numerical experiments using homogenous and heterogeneous model problems from nonlinear structural mechanics are provided. In the numerical experiments, we consider four standard choices of different elimination sets and different problem setups including stiff or almost incompressible inclusions in every subdomain. The numerical experiments illustrate that a good elimination set is important. However, the use of the SQP-based globalization approach presented here can improve the convergence of Nonlinear FETI-DP methods further, especially, if combined with a good choice of the elimination set.

Efficient partitioning of conforming virtual element discretizations for large scale discrete fracture network flow parallel solvers

Discrete Fracture Network models are largely used for large scale geological flow simulations in fractured media. For these complex simulations, it is worth investigating suitable numerical methods and tools for efficient parallel solutions on High Performance Computing systems. In this paper we propose and compare different partitioning strategies, that result to be highly efficient and scalable, overperforming the classical mesh partitioning approach used to balance the workload of a conforming mesh among several processes. The proposed DFN-based partitioning strategies rely on the distribution of the fractures among parallel processes. The computational cost of the DFN-based partitionings is very small compared to the cost of classical mesh partitioning and the numerical results prove their effectiveness and good performances in solving linear systems for realistic DFN flow simulations.

Heterogeneous Parallel Implementation of Large-Scale Numerical Simulation of Saint-Venant Equations

Large-scale floods are one of the major events that impact the national economy and people’s livelihood every year during the flood season. Predicting the factors of flood evolution is a worldwide problem. We use the two-dimensional Saint-Venant equations as an example and for high-performance computing in modelling the flood behavior. Discretization of the two-dimensional Saint-Venant equations with initial and boundary conditions with the finite difference method in the explicit leapfrog scheme is carried out. Afterwards, we employed a large-scale heterogeneous parallel solution on the “SunRising-1” supercomputer system using MPI, OpenMP, Pthread, and OpenCL runtime libraries. On this basis, we applied communication/calculation overlapping and the local memory acceleration to optimize the performance. Finally, various performance tests of the parallel scheme are carried out from different perspectives. We have found this method is efficient and recommend this approach be used in solving systems of partial differential equations similar to the Saint-Venant equations.

Вплив авторської програми фізичної підготовки на спортивні результати команд з військового п’ятиборства

The purpose of the study was to determine the impact of the author's program of physical training in military pentathlon on the sports readiness of teams. Materials and methods. To solve the goal, an experimental and control groups were formed, the results of special physical fitness of the subjects were determined, a comparative analysis of the indicators of competitive activity of athletes was carried out. The following methods were used to obtain objective data: theoretical methods (analysis and generalization of literature sources and empirical data); documentary method (analysis of official CISM documents); pedagogical methods (observation, experiment); testing the initial and final levels of general and special physical fitness of athletes; methods of mathematical statistics. The research was conducted in several stages with consistent and parallel solution of work tasks in the period from 2017 to 2019. The first stage (January 2017 – November 2017) was aimed at analyzing and summarizing data from special literature, publications and research. The second stage (November 2017 – November 2019) involved a formative pedagogical experiment, which tested the effectiveness of the author's program of physical training of pentathletes. To test the effectiveness of the experimental training program, experimental (n = 20) and control groups (n = 28) were formed, in which all cadets in military pentathlon had the same level of sports training. The cadets of Hetman Petro Sahaidachnyi National Ground Forces Academy (n = 20) were included in the experimental group, and the cadets of seven high educational institutions of Ukraine (n = 28) – in the control group. The distribution was based on the results of preliminary testing using the method of random sampling. Results and discussion. The results of the study confirmed that it is impossible to achieve high results in military pentathlon without continuous improvement of the organization, content and methods of implementation of this pedagogical process in the stages of preparation of military athletes for competitions. It is confirmed that one of the leading reasons for improving performance is related to the transfer of the training effect, namely the positive and sensitive period, which is characteristic of these physical qualities at the age stage in which the subjects were. Other reasons were related to the used load parameters planning, means and methods of training. The sports result of experimental group, namely the level of special physical fitness of the military pentathletes of the National Armed Forces in the conditions of the physical training program, significantly improved in the first (5.8%, p <0.05) and second (6.1%, p <0.05) stages of the study and as a result significantly increased by 11.5% (p <0.01). On the other hand, in the control groups 1-7 the tendency to increase sports results was not confirmed statistically. Conclusion. It has been proved that the author’s program of physical training of athletes in military pentathlon in the high educational institutions of the Armed Forces of Ukraine is not inferior to the traditional one in terms of efficiency. Significant differences (p <0.05 – p <0.001) in the amount of points scored at the Championship of the Armed Forces of Ukraine in military pentathlon between the participants of experimental and control groups (control group 1, control groups 3-7) after the end of the pedagogical experiment were determined

A non-overlapping domain decomposition method with perfectly matched layer transmission conditions for the Helmholtz equation

It is well-known that the convergence rate of non-overlapping domain decomposition methods (DDMs) applied to the parallel finite-element solution of large-scale time-harmonic wave problems strongly depends on the transmission condition enforced at the interfaces between the subdomains. Transmission operators based on perfectly matched layers (PMLs) have proved to be well-suited for configurations with layered domain partitions. They are shown to be a good compromise between basic impedance conditions, which can lead to slow convergence, and computational expensive conditions based on the exact Dirichlet-to-Neumann (DtN) map related to the complementary of the subdomain. Unfortunately, the extension of the PML-based DDM for more general partitions with cross-points (where more than two subdomains meet) is rather tricky and requires some care.In this work, we present a non-overlapping substructured DDM with PML transmission conditions for checkerboard (Cartesian) decompositions that takes cross-points into account. In such decompositions, each subdomain is surrounded by PMLs associated to edges and corners. The continuity of Dirichlet traces at the interfaces between a subdomain and PMLs is enforced with Lagrange multipliers. This coupling strategy offers the benefit of naturally computing Neumann traces, which allows to use the PMLs as discrete operators approximating the exact Dirichlet-to-Neumann maps. Two possible Lagrange multiplier finite element spaces are presented, and the behavior of the corresponding DDM is analyzed on several numerical examples.

Stochastic Optimal Device Sizing Model for Zero Energy Buildings: A Parallel Computing Solution

Byconsuming35% of the final global energy, buildings are among major contributors to greenhouse gas emissions and global warming. If the economic justification challenge is addressed, zero energy buildings (ZEB), which are defined as buildings that generate as much renewable-based energy as they consume annually, can be a promising solution for energy efficiency improvement in the building sector. In this article, we propose a stochastic ZEB device sizing model considering uncertain parameters (i.e., building's electrical and thermal demands, solar irradiation, and outdoor temperature) and their correlation. The proposed model finds the optimal size of the thermal and electrical devices considering their nonlinear behaviors and temperature-dependent dynamics. Furthermore, two parallel computing-based solution algorithms (i.e., parallelism in the algebraic level using Schur complement decomposition and parallelism in the problem (scenario) level by progressive hedging) are proposed to solve the stochastic model. Using the real historical data, numerical studies on the Woodward library building, located on the University of British Columbia campus, illustrate the efficacy of the solution algorithms to handle large-scale nonlinear programming models with more than 32.8 million variables, which is the largest one reported in the literature so far.

Improved thermal energy storage with metal foam enhanced phase change materials considering various pore arrangements: A pore-scale parallel lattice Boltzmann solution

Low thermal conductivity of the phase change materials (PCMs) is the main impediment that causes avoiding their extensive usage for thermal energy storage. Metal foams can be used with PCMs to overcome this weakness to reach an enhanced PCM. The main challenge of using metal foam is to reach the optimal geometrical, mechanical, and physical properties to meet the desired performance. This study investigates the effect of pore arrangement in a homogenous closed-cell aluminum metal foam. Afterward, a comparison is presented between various arrangements and pore diameters to examine the effect of pore configuration and diameter on thermal energy storage performance. Three pore arrangements are considered: Simple (simple linear arrangement of pores); Staggered (straticulate/alternative arrangement of pores); and Dots (simple pores with smaller ones diagonally placed between them). To simulate the melting process coupled with conduction and natural convection, the parallel lattice Boltzmann solver (PALABOS) –an open-source library consists of various predefined functions to solve complex thermo-fluidic problems– with enthalpy-based method is developed, and the results are validated. Different numerical simulations have been done to conduct the parameter study. In general, the Dots arrangement is relatively more effective than the two other studied arrangements. For dp = 5 mm, the melting times of PCM for all cases are similar to one another. However, for dp = 10 mm, the Dots arrangement could reduce the melting time by 20% compared to Staggered and Simple arrangements.

Mathematical models of a multi-criteria problem of reengineering topological structures of ecological monitoring networks

The article deals with the theoretical aspects of the problem of reengineering the topological structures of terrestrial ecological monitoring networks. As a result of the analysis of the current state of the problem, it was revealed the need to changethe network of monitoring points, to increaserequirements for the efficiency and accuracy of observations, as well as to do the more advanced technologies for collecting,processing, storing and transmitting information. All this is possible due to reengineering of existing monitoring networks. This requires the improvement of network system optimization technologies and their software in terms oftaking into account the features of the reengineering problem, as well as the mathematical models and methods used for this. To solve the problem of reengineering of terrestrial monitoring networks, an aggregative-decomposition approach is proposed. The approach is divided into a set of tasks considering their interconnections in terms of input and output data. This made it possible to define a set of tasks that form the basis of reengineering procedures. To increase the efficiency of technologies for computer-aided design and reengineering of networks, a set of mathematical models is proposed that covers the main stages of their life cycles. The article discusses: a systemological model of iterative technology for obtaining design solutions; analytical models for evaluating the properties of network reengineering options in terms of efficiency, reliability, survivability and costs; models for identifyingeffective options for network reengineering based on Karlin and Germeier theorems; a model for evaluating the local properties of options in the form of a utility function of local criteria; model of scalar multicriteria estimation of network reengineering options based on utility theory. The utility function makes it possible to implement both linear and non-linear (including Z-andS-shaped) dependencies on their values. For the practical implementation of modelsof multicriteria problems of reengineering of topological structures of networks, it is proposed to use the method of generation of effective design solutions in parallel with the generation and the method of comparator parametric synthesis of the scalar multicriteria estimation function. The performance and efficiencyof the proposed mathematical models and methods are demonstrated by examples of solving the problems of subset selection of Pareto-optimal options for building networks and parametric synthesis of the scalar multicriteria estimation function. The application in practice of the proposed set of models and methods will increase the degree of automation of network reengineering processes, reduce the time for solving the problem of multi-criteria choice due to the reduction in the time complexity of the analysis procedures, and increase the stability of the decisions made by compromising their choice only from a subset of effective ones.