Programming Problem Research Articles

Schemes designing for transport development of the forest tract by using information and intelligent systems

A model of computer-aided design of the transport network of timber highways, which allows improving the road design system is considered The features of the preparation of automated initial data are adduced and their advantages for solving a linear model of the timber transport network are shown through an experiment. Keywords logging road, design of a transport network, problem of a transport linear programming

Growth models with saturation in the problem of parametric programming as applied to agricultural production

Growth models with saturation in the problem of parametric programming as applied to agricultural production

Three different approaches to solving the problem of multicriteria fractional linear programming

Three different approaches to solving the problem of multicriteria fractional linear programming

Aspects of the Study of Genetic Algorithms and Mechanisms for their Optimization for the Travelling Salesman Problem

Lately, artificial intelligence has become increasingly popular. Still, at the same time, a stereotype has been formed that AI is based solely on neural networks, even though a neural network is only one of the numerous directions of artificial intelligence. This paper aims to bring attention to other directions of AI, such as genetic algorithms. In this paper, we study the process of solving the travelling salesman problem (TSP) via genetic algorithms (GA) and consider the issues of this method. The genetic algorithm is a method for solving both constrained and unconstrained optimization problems that are based on natural selection, the process that drives biological evolution. One of the common problems in programming is the travelling salesman problem. Many methods can be used to solve it, but we are going consider genetic algorithms. This study aims at developing the most efficient application of genetic algorithms in the travelling salesman problem.

Approach to optimizing charging infrastructure of autonomous trolleybuses for urban routes

P u r p o s e s. When designing a system of urban electric transport that charges while driving, including autonomous trolleybuses with batteries of increased capacity, it is important to optimize the charging infrastructure for a fleet of such vehicles. The charging infrastructure of the dedicated routes consists of overhead wire sections along the routes and stationary charging stations of a given type at the terminal stops of the routes. It is designed to ensure the movement of trolleybuses and restore the charge of their batteries, consumed in the sections of autonomous running.The aim of the study is to create models and methods for developing cost-effective solutions for charging infrastructure, ensuring the functioning of the autonomous trolleybus fleet, respecting a number of specific conditions. Conditions include ensuring a specified range of autonomous trolleybus running at a given rate of energy consumption on routes, a guaranteed service life of their batteries, as well as preventing the discharge of batteries below a critical level under various operating modes during their service life.M e t ho d s. Methods of set theory, graph theory and linear approximation are used.Re s u l t s. A mathematical model has been developed for the optimization problem of the charging infrastructure of the autonomous trolleybus fleet. The total reduced annual costs for the charging infrastructure are selected as the objective function. The model is formulated as a mathematical programming problem with a quadratic objective function and linear constraints.Co n c l u s i o n. To solve the formulated problem of mathematical programming, standard solvers such as IBM ILOG CPLEX can be used, as well as, taking into account its computational complexity, the heuristic method of "swarm of particles". The solution to the problem is to select the configuration of the location of the overhead wire sections on the routes and the durations of charging the trolleybuses at the terminal stops, which determine the corresponding number of stationary charging stations at these stops.

IMSD: Interactive Methods for Finding Similar or Diverse Answer Sets

Answer set programming (ASP) is a modeling language in knowledge representation, rooted in Logic Programming and Nonmonotonic Reasoning, which has been gaining increasing attention during the last years. In recent years, many of the researchers developed integrated development environments (IDE) for ASP programs including editors and debuggers. Other researchers focused on analyzing the answer sets, they introduced offline and online methods to find specific solutions of a given problem in answer set programming in different approaches such as phylogeny reconstruction. However, with an enormous number of answer sets could be available, the user is not interested in all of them. Thus, a navigation of the search space could be a solution to help the user to access the specific answer sets. To this end, we aim at finding similar/diverse solutions of the answer sets with a new method. The intuition behind this navigation is to make the search faster than other methods and explore information that is related to the user’s query. Afterward, we implement a tool performing the above approach in order to simplify the search task and show the applicability and effectiveness of our method. We conclude by testing the performance of the proposed tool into a real-world example of ASP programs.

IMSD: Interactive Methods for Finding Similar or Diverse Answer Sets

Answer set programming (ASP) is a modeling language in knowledge representation, rooted in Logic Programming and Nonmonotonic Reasoning, which has been gaining increasing attention during the last years. In recent years, many of the researchers developed integrated development environments (IDE) for ASP programs including editors and debuggers. Other researchers focused on analyzing the answer sets, they introduced offline and online methods to find specific solutions of a given problem in answer set programming in different approaches such as phylogeny reconstruction. However, with an enormous number of answer sets could be available, the user is not interested in all of them. Thus, a navigation of the search space could be a solution to help the user to access the specific answer sets. To this end, we aim at finding similar/diverse solutions of the answer sets with a new method. The intuition behind this navigation is to make the search faster than other methods and explore information that is related to the user’s query. Afterward, we implement a tool performing the above approach in order to simplify the search task and show the applicability and effectiveness of our method. We conclude by testing the performance of the proposed tool into a real-world example of ASP programs.

APPLICATION OF OFFICE INFORMATION TECHNOLOGIES TO SOLVE THE PROBLEMS OF OPTIMAL STRUCTURAL RESERVATION OF SYSTEMS

Problem statement. The problems of optimal structural redundancy of systems are usually formulated as a nonlinear problem of mathematical programming with integer variables, and to solve them, usually, various optimization methods are used, which requires the development of special algorithms and appropriate software. However, in the case of clarifying the original task of optimal redundancy, there is often a need to adjust the developed algorithms and software. All this greatly complicates obtaining the desired results. Another approach to solving problems of optimal redundancy of systems is the use of office information technology, the tool environment of which is adapted to solve mathematical problems, including optimization problems. This approach does not require the development of special algorithms and software. However, issues related to the effectiveness of the information technology used to solve this problem require further scientific and practical study. This article formulates a model of optimal design of redundant systems according to the criterion of minimum cost while ensuring the required level of reliability during a given time. This model is written in terms of a nonlinear problem of mathematical programming with integer variables and is numerically implemented in the operating environment of an Excel spreadsheet when the main object of the designed system consists of 6 elements. The optimal options for reserving this object according to the schemes of "hot" and "cold" redundancy are obtained. The purpose of the article is to show the effectiveness and efficiency of the MS Excel spreadsheet to solve problems of optimal structural redundancy of systems. Conclusions. This article discusses issues related to the problem of solving problems of optimal design of redundant systems in the tool environment of the MS Excel spreadsheet. Examples of solving the problems of separate "hot" and separate "cold" redundancy of a 6-element object prove the effectiveness and efficiency of the MS Excel spreadsheet to solve this problem. In addition, the developed optimization model can be successfully used in practical tasks to ensure the reliability of technical systems in the early stages of their design.

Impact of Demand Response on Reliability Enhancement in Distribution Networks

This paper presents an innovative instantaneous pricing scheme for optimal operation and improved reliability for distribution systems (DS). The purpose of the proposed program is to maximize the operator’s expected profit under various risk-taking conditions, such that the customers pay the minimum cost to supply energy. Using the previous information of the energy consumption for each customer, a customer baseline load (CBL) is defined; the energy price for consumption costs higher and lower than this level would be different. The proposed scheme calculates the difference between the baseline load and the consumption curve with the electricity market price instead of calculating the total consumption of the customers with the unstable price of the electricity market, which is uncertain. In the proposed tariff, the developed cost and load models are included in the distribution system operation problem, and the objective function is modeled as a mixed integer linear programming (MILP) problem. Also, the effect of demand response (DR) and elasticity on the load curve, the final profit of the distribution system operator, and payment risk and operation costs are examined. Since there are various uncertainties in the smart distribution grid, the calculations being time-consuming and volumetric is important in the evaluation of reliability indices. Thus, when computation volume can be decreased and computation speed can be increased, analytical reliability analysis methods can be used, as they were in the present work. Finally, the changes in the reliability indices were calculated for the ratio of the customers’ sensitivity to the price and the customers’ participation in the proposed tariff using an analytical method based on Monte Carlo simulation (MCS). The results showed the efficiency of the proposed method in increasing the operator profit, reducing the operation costs, and enhancing the reliability indices.

Application and Comparative Study of Optimization Algorithms in Financial Investment Portfolio Problems

Portfolio theory mainly studies how to optimize the allocation of assets under the premise of maximizing expected returns and minimizing investment risks. In view of the instability of the financial market, a diversified investment portfolio can help control the loss of the investment portfolio. In addition to paying attention to the safety and return of asset allocation, we cannot ignore the liquidity of assets, that is, their liquidity. Adding high-liquidity products to asset allocation, such as equity investment, can better control the financial cash flow in response to emergencies. One of the ways to make assets flow is to securitize assets and sell them to the market. In order to revitalize the stock assets, good investment efficiency is a necessary choice for financial investment. Various financial products and their derivatives continue to enter people’s vision. There are many financial products in reality, and optimizing the investment portfolio can bring high economic benefits. The purpose of this paper is to study the application of optimization algorithms in financial portfolio problems. (1) Monetary policy remains prudent and neutral. It is not easy to expect flooding, but flexibility is required in complex situations. (2) Financial resources are tilted towards innovation and transformation and capital markets, which is beneficial to the development of capital markets in the medium and long term. (3) Unblocking the transmission mechanism is conducive to lenient credit and tapping the wrong killing opportunities in private enterprise debt. (4) Banks and other financial institutions have moderate pressure to give benefits to entities, but in the long run, the interests of the two are consistent. (5) Finance risk prevention will continue, orderly breaking the rigid exchange and reshaping the financial structure and ecology. (6) The pace of opening up of the financial industry has accelerated, and the bond market investor structure has improved. In this paper, we establish different optimization schemes to compare and study the portfolio problem and then use MATLAB to solve the modeling and programming problem, calculate the highest return rate and the lowest risk value before and after optimization, and then make a comparative analysis to get a better optimization scheme. The results show that the genetic algorithm model is superior to the quadratic programming method in terms of risk control. The minimum risk of portfolio optimization through genetic algorithm has been reduced by about 40%, and the maximum return has increased by about 25%. The comprehensive optimization effect is better than the quadratic planning method and ultimately can obtain higher economic benefits. It can be seen that the optimization algorithm is of great significance for the comparative study of financial portfolio problems.

Формирование оптимального комплекта программного обеспечения в образовательных организациях

The problem of determining the nomenclature of the optimal set of application software (software) necessary for the implementation of educational programs in higher educational institutions (HEI) by quantifying its quality is considered. Aim. Development of a mechanism for a comprehensive assessment of the quality of software within the selected class, to simplify the task of making an informed decision when choosing a standard set of universities. Materials and methods. The proposed mechanism is based on the use of optimization methods and expert assessments. At the first stage of the mechanism, the basic requirements are clarified, taking into account the specifics of the work of the educational organization. A set of programs (alternatives) for the selected software class is formed, with the subsequent determination of the key functions characteristic of it on the basis of expert information. Further, according to the software quality indicators proposed in the work, they are evaluated for each alternative. Software quality indicators are a hierarchical three-level system (criterion, metric, evaluation element), in which the indicators of the higher levels are determined through the indicators of the lower levels. The integral assessment of the quality of an alternative is defined as the sum of the estimates of its quality criteria. At the final stage, the problem of integer linear programming is solved to determine the optimal range of alternatives within the corresponding software class, based on their conditions: maximizing the quality of an alternative contai¬ning the required set of functions, and minimizing their number. Results. The mechanism of determining the optimal alternatives for the formation of a standard set of software, in order to implement the necessary educational programs of the university, is considered. The main indicators of software quality and the mathematical apparatus for their assessment are formalized. Conclusion. The proposed mechanism allows for a quantitative assessment of the quality of software within its class, with the subsequent selection of the most rational software tools for the university. Such an asses¬sment will simplify the task of making an informed decision when forming a standard set of software necessary for implementing the requirements of federal educational standards, and in general will increase the effectiveness of the system for coordinating informatization in this direction.

Lifetime Maximization for 5G Mobile Networks Using Secured and Finest Optimal Routing Protocol

The lifetime enhancement of any 5G Wireless Networks is essential to increase the efficacy and also the network performance. Hence, to enhance the lifetime, identifying a reliable routing protocol is the major challenge in any wireless network. In this proposed research, combined optimization technique named Secured and Finest Optimal Routing (SFOR) protocol is proposed to increase the network lifetime. Therefore, the given scenario is configured as Software Defined Network (SDN) which will configure the network dynamically for efficient management. Three scenario’s of the routing problem is arrived once, the routing of the mobile node is unidentified to derive a SFOR for maximizing the network lifetime. The arrived three scenario’s are mathematically modeled as Linear Programming (LP) problem and the problems are resolved utilizing the source node routing strategies. In this research work, the planned SFOR procedure is deployed in addition efficacy is associated through the reported methods. It is detected that the projected SFOR procedure increases the era of the network is 16% and 50% as compared with Virtual Ad hoc Routing Protocol and Path Collection constructed on Trust Protocol respectively.

Devising a method for the formation of sustainable chains of supply of raw materials from mercantile exchange to a timber processing enterprise considering uncertainties and risks

The relevant problem of guaranteed supply of high-quality raw materials to a timber processing enterprise that does not have its own sources of raw materials is considered. A method for the formation of sustainable chains of supplying raw materials to a timber processing enterprise was proposed, taking into consideration uncertainties and risks associated with the purchase of raw materials on the mercantile exchange and the implementation of the circuit of delivery to a warehouse. A dynamic model, which is a problem of stochastic nonlinear programming, the objective function of which is the cost of purchasing raw materials, was developed. The model makes it possible to form a plan for purchasing raw materials on the timber section of the mercantile exchange on a given planning horizon, taking into consideration uncertainties when it comes to the number of daily offers, their volumes, and prices. The risk of cancellation of the concluded contract due to the loss of the quality of raw materials during delivery and non-fulfillment of delivery terms was also taken into consideration. To find a solution to the model, a two-stage circuit, in which the first stage involves a procurement plan that is close to optimal, was proposed. At the second stage, a plan that is closest to the basic one in terms of the volume of purchased raw materials and minimizing the total costs is chosen for each day of implementation of a random flow of applications. The numerical solution at the first stage is found using the heuristic algorithm that uses the branch and bound method and the genetic algorithm at certain steps. At the second stage, the multi-criteria problem of mathematical programming is solved numerically. An example of the formation by a timber processing enterprise in the Far East of a suboptimal procurement plan that ensures an increase in the efficiency and sustainability of economic activity in the long term is considered

Determining configuration parameters for proportionally integrated differentiating controllers by arranging the poles of the transfer function on the complex plane

This paper reports a solution to the problem of determining the configuration parameters of PID controllers when arranging the poles of the transfer function of a linear single-circuit automated control system for a predefined set of control objects. Unlike known methods in which the task to find the optimal settings of a PID controller is formed as a problem of nonlinear programming, in this work a similar problem is reduced to solving a system of linear algebraic equations. The method devised is based on the generalized Viète theorem, which establishes the relationship between the parameters and roots of the characteristic equation of the automatic control system. It is shown that for control objects with transfer functions of the first and second orders, the problem of determining the configuration parameters of PID controllers has an unambiguous solution. For control objects with transfer functions of the third and higher orders, the generated problem is reduced to solving the redefined system of linear algebraic equations that has an unambiguous solution when the Rouché–Capelli theorem condition is met. Such a condition can be met by arranging one of the roots of the characteristic equation of the system on a complex plane. At the same time, the requirements for the qualitative indicators of the system would not always be met. Therefore, alternative techniques have been proposed for determining the configuration parameters of PID controllers. The first of these defines configuration parameters as a pseudo solution to the redefined system of linear algebraic equations while the second produces a solution for which the value of the maximum residual for the system of equations is minimal. For each case, which was used to determine the settings of PID controllers, such indicators of the control process as overshooting and control time have been determined

Enabling In-Depot Automated Routing and Recharging Scheduling for Automated Electric Bus Transit Systems

The bus transit system is promising to enable electric and autonomous vehicles for massive urban mobility, which relies on high-level automation and efficient resource management. Besides the on-road automation, the in-depot automated scheduling for battery recharging has not been adequately studied yet. This paper presents an integrated in-depot routing and recharging scheduling (IDRRS) problem, which is modeled as a constraint programming (CP) problem with Boolean satisfiability conditions (SAT). The model is converted to a flexible job-shop problem (FJSP) and is feasible to be solved by a CP-SAT solver for the optimal solution or feasible solutions with acceptable performance. This paper also presents a case study in Shanghai and compares the results from the FJSP model and the first-come first-serve (FCFS) method. The result demonstrates the allocation of routes and chargers under multiple scenarios with different numbers of chargers. The results show that the FJSP model shortens the delay and increases the time conservation for future rounds of operation than FCFS, while FCFS presents the simplicity of programming and better computational efficiency. The multiple random input test suggests that the proposed approach can decide the minimum number of chargers for stochastic charging requests. The proposed method can conserve the investment by increasing the utilization of automated recharging devices, improving vehicles’ in-depot efficiency.

Secrecy Rate of Resource-Constrained Mobile Relay Model under Two-Way Wiretap Channel

Relay communication is emerging as a promising solution to improving the reliability of long-distance communication systems. However, transmitting data in a secure way is challenging due to the possibility of eavesdroppers wiretapping such systems. To address the challenge, this paper proposes a joint secure transmission and graph mobility model. With the proposed model, the secrecy rate of the resource-constrained two-way wiretap channel mobile relay system is formulated as a mixed integer nonlinear programming (MINLP) problem. Furthermore, efficient algorithms that achieve a local optimal solution are derived. Numerical results are provided to validate the performance of the proposed algorithms.

Pedestrian Bridge Application in a Fundamentals of Structural Analysis Course Inside an Architecture Bachelor Program

The paper presents an application of the Problem-Based Learning (PBL) methodology in a structural analysis course taught in English of the third year Architecture bachelor program at Politecnico di Torino (Italy). This experimentation regards a class which is composed mostly of international students, that is, a heterogeneous audience with different background. In general, students struggle with the technical aspects typical of structural analysis course. PBL has been found as a possible solution to this problem in Engineering programs. The aim of redesigning the course is to support students’ learning while evaluating the PBL application in a non-technical context with an international audience. This article describes the structure and the results of the PBL implementation. In particular, the participation has increased compared to the previous academic year in terms of presence during the lectures, interest in the subject, interaction between the lecturer and the students, and exams’ results. These results are encouraging and confirm the validity of the PBL methodology as actually applied.

Verification of Approximate Opacity via Barrier Certificates

This paper is motivated by the increasing security concerns of cyber-physical systems. Here, we develop a discretization-free verification scheme targeting an information-flow security property, called approximate initial-state opacity, for the class of discrete-time control systems. We propose notions of so-called augmented control barrier certificates in conjunction with specified regions of interest capturing the initial and secret sets of the system. Sufficient conditions for (the lack of) approximate initial-state opacity of discrete-time control systems are proposed based on the existence of the proposed barrier certificates. We further present an efficient computation method by casting the conditions for barrier certificates as sum-of-squares programming problems. The effectiveness of the proposed results is illustrated through two numerical examples.

The Comparison of China and Iran Response to COVD-19 Pandemic: Lessons Learn for Health Policy

ABSTRACT Currently, despite the change in the course of diseases, attention to infectious diseases and their integration has decreased. The prevalence of remerging infectious diseases has led to the need for appropriate preparation programs. There are still problems in controlling infectious diseases with the outbreak of coronavirus. The outbreak of the disease affected many countries in a short period. Therefore, by examining the actions of the two countries, it is possible to gain appropriate experiences in dealing with infectious diseases. This study was conducted using a gray literature review to examine all applied actions for the response to COVID-19 epidemics and their impacts on the prevalence of this disease in China and Iran. Examination of the documents shows that disease prevention is the most critical action, and we have witnessed a decrease in the number of patients with this disease by the introduction of prevention policies. The implementation problems of quarantine programs were meeting the basic needs of the people and continuing to implement this program. The issue of education was also one of the leading problems.

Examination of Daily Task Constraint in Technician Routing and Scheduling Problem

This paper deals with a multi-term technician routing and programming problem with a different concept. The problem is that technicians with various skills form teams, and these teams perform the tasks that take in distinct locations. Technicians have daily duty capacities while performing tasks. The cases where overtime costs are allowed by combining different technician numbers are analyzed. Paper provides a single-purpose mixed integer programming method for modeling the problem because the model implemented aims to optimize the travel cost while simultaneously minimizing the amount of overwork. The main issue also specifies the division of technicians with different skills into teams, assignment of tasks with different skill requirements to teams, and routes for each team at the same time. The number of customers visited on a route within the daily customer limit. In addition, the model included exceeding the daily customer limit in the model and bound it to a constraint. The various combinations of the daily normal and over-work number of customers were evaluated and examined their effects on the objective function. Finally, the paper presents computational experiments and analyses to evaluate the efficiency of the proposed mathematical formulation and solution approach. The results show that daily task constraints are effective in employee selection and amount of use.