Author explains a necessity of supply optimization to construction sites with small storage areas. This paper takes account of conditions existing in Poland. From among all factors discussed by the author, first of all, we should point at construction works on plots located in densely built-up areas, obtained by demolition of existing buildings, as well as a necessity of plots utilization after demolished buildings that technical conditions do not allow for further exploitation.
The aim of the presented paper is to show the results of shape optimization of railway polynomial transition curves (TCs) of 5th, 7th, and 9th degrees through the use of the full vehicle model and new criteria of assessement concerning the jerk value. The search for the proper shape of TCs means that in this work, the evaluation of TC properties is based on select quantities and the generation of such a shape through the use of mathematically understood optimization methods. The studies presented have got a character of the numerical tests. For this work, advanced vehicle models describing dynamical track-vehicle and vehicle-passenger interactions as well as optimization methods were exploited. In the software vehicle model of a 2-axle freight car, the track discrete model, non-linear descriptions of wheel-rail contact are applied. This part of the software, the vehicle simulation software, is combined with a library optimization procedure into the final computer program.
This paper presents a model of scheduling of multi unit construction project based on an NP-hard permutation flow shop problem, in which the considered criterion is the sum of the costs of the works' execution of the project considering the time of the project as a constraint. It is also assumed that each job in the units constituting the project may be realized in up to three different ways with specific time and cost of execution. The optimization task relies on solving the problem with two different decision variables: the order of execution of units (permutation) and a set of ways to carry out the works in units. The task presented in the paper is performed with the use of a created algorithm which searches the space of solutions in which metaheuristic simulated annealing algorithm is used. The paper presents a calculation example showing the applicability of the model in the optimization of sub-contractors' work in the construction project.
In this paper, the applications of the multivariate data analysis and optimization on vibration signals from compressors have been tested on the assembly line to identify nonconforming products. The multivariate analysis has wide applicability in the optimization of weather forecasting, agricultural experiments, or, as in this case study, in quality control. The techniques of discriminant analysis and linear program were used to solve the problem. The acceleration and velocity signals used in this work were measured in twenty-five rotating compressors, of which eleven were classified as good baseline compressors and fourteen with manufacturing defects by the specialists in the final acoustic test of the production line. The results obtained with the discriminant analysis separated the conforming and nonconforming groups with a significance level of 0.01, which validated the proposed methodology.
The aim of this study is to find the cost design of RC tension with varying conditions using the Artificial Neural Network. Design constraints were used to cover all reliable design parameters, such as limiting cross sectional dimensions and; their reinforcement ratio and even the beahviour of optimally designed sections. The design of the RC tension members were made using Indian and European standard specifications which were discussed. The designed tension members according to both codes satisfy the strength and serviceability criteria. While no literature is available on the optimal design of RC tension members, the cross-sectional dimensions of the tension membersfor different grades of concrete and steel, and area of formwork are considered as the variables in the present optimum design model. A design example is explained and the results are presented. It is concluded that the proposed optimum design model yields rational, reliable, and practical designs.
This paper presents the resolution of the optimal reactive power dispatch (ORPD) problem and the control of voltages in an electrical energy system by using a hybrid algorithm based on the particle swarmoptimization (PSO) method and interior point method (IPM). The IPM is based on the logarithmic barrier (LB-IPM) technique while respecting the non-linear equality and inequality constraints. The particle swarmoptimization-logarithmic barrier-interior point method (PSO-LB-IPM) is used to adjust the control variables, namely the reactive powers, the generator voltages and the load controllers of the transformers, in order to ensure convergence towards a better solution with the probability of reaching the global optimum. The proposed method was first tested and validated on a two-variable mathematical function using MATLAB as a calculation and execution tool, and then it is applied to the ORPD problem to minimize the total active losses in an electrical energy network. To validate the method a testwas carried out on the IEEE electrical energy network of 57 buses.
A transformer is an important part of power transmission and transformation equipment. Once a fault occurs, it may cause a large-scale power outage. The safety of the transformer is related to the safe and stable operation of the power system. Aiming at the problem that the diagnosis result of transformer fault diagnosis method is not ideal and the model is unstable, a transformer fault diagnosis model based on improved particle swarm optimization online sequence extreme learning machine (IPSO-OS-ELM) algorithm is proposed. The improved particle swarmoptimization algorithm is applied to the transformer fault diagnosis model based on the OS-ELM, and the problems of randomly selecting parameters in the hidden layer of the OS-ELM and its network output not stable enough, are solved by optimization. Finally, the effectiveness of the improved fault diagnosis model in improving the accuracy is verified by simulation experiments.
In the last decade, Poland has become one of the most active markets for unconventional hydrocarbon deposits exploration. At present, there are twenty concessions for the exploration and/or discovery of reserves, including shale gas. The area covered by exploration concessions constitutes ca. 7.5% of the country’s area. Four main stages can be distinguished In the shale gas development and exploitation project: the selection and preparation of the place of development of the wells, hydraulic drilling and fracturing, exploitation (production) and marketing, exploitation suppression and land reclamation. In the paper, the concept of cost analysis of an investment project related to the exploration and development of a shale gas field/area was presented. The first two stages related to the preparatory work, carried out on the selected site, as well as drilling and hydraulic fracturing were analyzed. For economic reasons, the only rational way to make shale gas reserves available is to use horizontal drilling, either singly or in groups. The number of drilling pads covering the concession area is a fundamental determinant of the development cost of the deposit. In the paper, the results of the cost analysis of various types of reaming method with an area of 25,000,000 m2 were presented. Cost estimates were prepared for two variants: group drilling for three types of drilling pads: with three, five and seven wells and for single wells. The results show that, as the number of horizontal wells increases, the total cost of the development of the deposit is reduced. For tree-wells pad, these costs are 7% lower than in the second variant, for five-well pads they are 11% lower, and for seven-well pads they are 11.5% smaller than in the second variant. Authors, using applied methodology, indicate the direction of further research that will enable the optimization of shale gas drilling operations.
This article considers designing of a renewable electrical power generation system for self-contained homes away from conventional grids. A model based on a technique for the analysis and evaluation of two solar and wind energy sources, electrochemical storage and charging of a housing area is introduced into a simulation and calculation program that aims to decide, based on the optimized results, on electrical energy production system coupled or separated from the two sources mentioned above that must be able to ensure a continuous energy balance at any time of the day. Such system is the most cost-effective among the systems found. The wind system adopted in the study is of the low starting speed that meets the criteria of low winds in the selected region under study unlike the adequate solar resource, which will lead to an examination of its feasibility and profitability to compensate for the inactivity of photovoltaic panels in periods of no sunlight. That is a system with fewer photovoltaic panels and storage batteries whereby these should return a full day of autonomy. Two configurations are selected and discussed. The first is composed of photovoltaic panels and storage batteries and the other includes the addition of a wind system in combination with the photovoltaic system with storage but at a higher investment cost than the first. Consequently, this result proves that is preferable to opt for a purely photovoltaic system supported by the storage in this type of site and invalidates the interest of adding micro wind turbines adapted to sites with low wind resources.
The locally resonant sonic material (LRSM) is an artificial metamaterial that can block underwater sound. The low-frequency insulation performance of LRSM can be enhanced by coupling local resonance and Bragg scattering effects. However, such method is hard to be experimentally proven as the best optimizing method. Hence, this paper proposes a statistical optimization method, which first finds a group of optimal solutions of an object function by utilizing genetic algorithm multiple times, and then analyzes the distribution of the fitness and the Euclidean distance of the obtained solutions, in order to verify whether the result is the global optimum. By using this method, we obtain the global optimal solution of the low-frequency insulation of LRSM. By varying parameters of the optimum, it can be found that the optimized insulation performance of the LRSM is contributed by the coupling of local resonance with Bragg scattering effect, as well as a distinct impedance mismatch between the matrix of LRSM and the surrounding water. This indicates coupling different effects with impedance mismatches is the best method to enhance the low-frequency insulation performance of LRSM.
The problem of optimally controlling a Wiener process until it leaves an interval (a; b) for the first time is considered in the case when the infinitesimal parameters of the process are random. When a = ��1, the exact optimal control is derived by solving the appropriate system of differential equations, whereas a very precise approximate solution in the form of a polynomial is obtained in the two-barrier case.
The article deals with the patterns of segmental adaptation of Polish voiceless affricates in initial and fi nal CC (consonant + consonant) clusters by native speakers of English. The data have been collected in an online loanword adaptation experiment in which 30 native speakers of Southern British English reproduced Polish words containing such sequences. The major problem posed by the data is the divergent adaptation of the post-alveolar /͡tʂ/ vs. the pre-palatal /͡tɕ/, with the former substituted mainly with the coronal plosive [t] and the latter realised as the palato-alveolar affricate [͡tʃ]. It is argued that these patterns of nativisation are due to the highlyranked IDENT-IO[dist] constraint, which militates against the modifi cation in the value of the feature [distributed]. Furthermore, it is demonstrated that the experimental results provide evidence in favour of the fundamental assumptions underlying the phonological approach to loan assimilation, namely the phonological input view as well as the faithful perception view.
Transport is one of the factors influencing the development of metropolitan areas. However, for its efficient work, numerous optimizations are required. Main tasks are shortening travel time, improving service quality and increasing the number of passengers served. The author has presented current studies on the field in optimization of public transport, mainly ways to optimize the transport network construction, based on large data sets about the population and their communication behaviour. Methods of combining various types of public transport with each other are presented. In the paper also are presents authors studies on the communication accessibility within the city of Cracow. Estimated distances from buildings to various types of public transport stops. The results were presented in aggregated form. Calculated communication speed of three types of public transport functioning in Cracow has also been discussed.
Hybrid Renewable Energy Systems connected to the traditional power suppliers are an interesting technological solution in the field of energy engineering and the integration of renewable systems with other energy systems can significantly increase in energy reliability. In this paper, an analysis and optimization of the hybrid energy system, which uses photovoltaic modules and wind turbines components connected to the grid, is presented. The system components are optimized using two objectives criteria: economic and environmental. The optimization has been performed based on the experimental data acquired for the whole year. Results showed the optimal configuration for the hybrid system based on economical objective, that presents the best compromise between the number of components and total efficiency. This achieved the lowest cost of energy but with relatively high CO2 emissions, while environmental objective results with lower CO2 emissions and higher cost of energy and presents the best compromise between the number of components and system net present cost. It has been shown that a hybrid system can be optimized in such a way that CO2 emission is maximally reduced and – separately – in terms of reducing the cost. However, the study shows that these two criteria cannot be optimized at the same time. Reducing the system cost increase CO2 emission and enhancing ecological effect makes the system cost larger. However, depends on strategies, a balance between different optimization criteria can be found. Regardless of the strategy used economic criteria – which also indirect takes environmental aspects as a cost of penalties – should be considered as a major criterion of optimization while the other objectives including environmental objectives are less important.
The computing performance optimization of the Short-Lag Spatial Coherence (SLSC) method applied to ultrasound data processing is presented. The method is based on the theory that signals from adjacent receivers are correlated, drawing on a simplified conclusion of the van Cittert-Zernike theorem. It has been proven that it can be successfully used in ultrasound data reconstruction with despeckling. Former works have shown that the SLSC method in its original form has two main drawbacks: time-consuming processing and low contrast in the area near the transceivers. In this study, we introduce a method that allows to overcome both of these drawbacks. The presented approach removes the dependency on distance (the “lag” parameter value) between signals used to calculate correlations. The approach has been tested by comparing results obtained with the original SLSC algorithm on data acquired from tissue phantoms. The modified method proposed here leads to constant complexity, thus execution time is independent of the lag parameter value, instead of the linear complexity. The presented approach increases computation speed over 10 times in comparison to the base SLSC algorithm for a typical lag parameter value. The approach also improves the output image quality in shallow areas and does not decrease quality in deeper areas.
This research presents a comparative study for maximum power point tracking (MPPT) methodologies for a photovoltaic (PV) system. A novel hybrid algorithm golden section search assisted perturb and observe (GSS-PO) is proposed to solve the problems of the conventional PO (CPO). The aim of this new methodology is to boost the efficiency of the CPO. The new algorithm has a very low convergence time and a very high efficiency. GSS-PO is compared with the intelligent nature-inspired multi-verse optimization (MVO) algorithm by a simulation validation. The simulation study reveals that the novel GSS-PO outperforms MVO under uniform irradiance conditions and under a sudden change in irradiance.
Games are among problems that can be reduced to optimization, for which one of the most universal and productive solving method is a heuristic approach. In this article we present results of benchmark tests on using 5 heuristic methods to solve a physical model of the darts game. Discussion of the scores and conclusions from the research have shown that application of heuristic methods can simulate artificial intelligence as a regular player with very good results.
In the paper an approach to decision making in situations with non-point-like characterisation and subjective evaluation of the actions is considered. The decision situation is represented mathematically as fuzzy multiobjective linear programming (fMOLP) model, where we apply the reduced fuzzy matrices instead of fuzzy classical numbers. The fMOLP model with reduced parameters is decomposable into the set of point-like models and the point-like models enable effective construction of an optimisation procedure – fBIP, see Wojewnik (2006ab), extending the bireference procedure by Michalowski and Szapiro (1992). The approach is applied to a fuzzy optimization problem in the area of telecommunication services.
This paper presents a new modified method for the synthesis of non-uniform linear antenna arrays. Based on the recently developed invasive weeds optimization technique (IWO), the modified invasive weeds optimization method (MIWO) uses the mutation process for the calculation of standard deviation (SD). Since the good choice of SD is particularly important in such algorithm, MIWO uses new values of this parameter to optimize the spacing between the array elements, which can improve the overall efficiency of the classical IWO method in terms of side lobe level (SLL) suppression and nulls control. Numerical examples are presented and compared to the existing array designs found in the literature, such as ant colony optimization (ACO), particle swarm optimization (PSO), and comprehensive learning PSO (CLPSO). Results show that MIWO method can be a good alternative in the design of non-uniform linear antenna array.
In order to overcome the shortcomings of the dolphin algorithm, which is prone to falling into local optimum and premature convergence, an improved dolphin swarm algorithm, based on the standard dolphin algorithm, was proposed. As a measure of uncertainty, information entropy was used to measure the search stage in the dolphin swarm algorithm. Adaptive step size parameters and dynamic balance factors were introduced to correlate the search step size with the number of iterations and fitness, and to perform adaptive adjustment of the algorithm. Simulation experiments show that, comparing with the basic algorithm and other algorithms, the improved dolphin swarm algorithm is feasible and effective.
The problem that this paper investigates, namely, optimization of overlay computing systems, follows naturally from growing need for effective processing and consequently, fast development of various distributed systems. We consider an overlay-based computing system, i.e., a virtual computing system is deployed on the top of an existing physical network (e.g., Internet) providing connectivity between computing nodes. The main motivation behind the overlay concept is simple provision of network functionalities (e.g., diversity, flexibility, manageability) in a relatively cost-effective way as well as regardless of physical and logical structure of underlying networks. The workflow of tasks processed in the computing system assumes that there are many sources of input data and many destinations of output data, i.e., many-to-many transmissions are used in the system. The addressed optimization problem is formulatedin the form of an ILP (Integer Linear Programing) model. Since the model is computationally demanding and NP-complete, besides the branch-and-bound algorithm included in the CPLEX solver, we propose additional cut inequalities. Moreover, we present and test two effective heuristic algorithms: tabu search and greedy. Both methods yield satisfactory results close to optimal.
The 802.11ax standard final specification is expected in 2019, however first parameters are just released. The target of the new standard is four times improvement of the average throughput within the given area. This standard is dedicated for usage in dense environment such as stadiums, means of municipal communication, conference halls and others. The main target is to support many users at the same time with the single access point. The question arises if the new standard will have higher throughput then previous ones in the single user mode. The author calculated the maximal theoretical throughput of the 802.11ax standard and compared the results with the throughput of older 802.11 standards such as 802.11n and 802.11ac. The new he-wifi-network example included in the ns-3.27 release of the NS-3 simulator was used to simulate the throughput between the access point and the user terminal. The results indicate that in some conditions the 802.11ac standard has higher throughput than the new 802.11ax standard.
Within the boundaries of many municipal urbanized areas, large grounds are found, from which the noise is emitted into the environment, surrounded by the regions liable to acoustic protection. Such a condition generates many problems including also those ones related to the lack of the fulfillment of requirements concerning environmental protection against excessive noise. Therefore the aim of vital importance is the proper management of municipal grounds, both in view of the investment in policy steering, especially of new investments, and in the case of activities aimed at maintaining or restoring (revitalizing) the acoustic properties on the grounds that have already been used or simply degraded before. Keeping the scale of the problem in mind, such activities must be carried on not temporarily, but must have a systemic character. The structure of every system is characterized by the appropriate relationships among their elements and the properties of those relationships. In case of the noise management system, the elements of such a system are the activities connected with the management itself that are the actions which rely on specifying the aims and causing their realization within the scope and on the grounds subject to the managing entity. The superior aim of such activities should be to supply the tools for improvement of management and in the process of taking decisions that relate to investments including the of optimization conditions and maintenance of socio-economic importance of such areas.
The multicriteria decision process consists of five main steps: definition of the optimisation problem, determination of the weight structure of the decision criteria, design of the evaluation matrix, selection of the optimal evaluation method and ranking of solutions. It is often difficult to obtain the optimal solution to a multicriterion problem. The main reason is the subjective element of the model – the weight functions of the decision criteria. Expert opinions are usually taken into account in their determination. The aim of this article is to present a novel method of minimizing the uncertainty of the weights of the decision criteria using Monte Carlo simulation and method of data reconciliation. The proposed method is illustrated by the example of multicriterion social effectiveness evaluation for electric power supply to a building using renewable energy sources.
Organic Rankine cycle (ORC) is used, amongst the others, in geothermal facilities, in waste heat recovery or in domestic combined heat and power (CHP) generation. The paper presents optimization of an idealized ORC equivalent of the Carnot cycle with non-zero temperature difference in heat exchangers and with energy dissipation caused by the viscous fluid flow. In this analysis the amount of heat outgoing from the ORC is given. Such a case corresponds to the application of an ORC in domestic CHP. This assumption is different from the most of ORC models where the incoming amount of heat is given.