Search results for: pareto optimal solution

Authors: Mohammad Reza Shahnazari, Reza Kazemi, Ali Saberi

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Most of the engineering problems are in nonlinear forms. Nonlinear boundary layer problems defined in infinite intervals contain specific complexities, especially in boundary layer condition conformance. As an example of these nonlinear complex problems, the well-known Blasius equation can be mentioned, which itself is one of the classic boundary layer problems. No analytical solution has been proposed yet for the Blasius equation due to its complexity. In this paper, an analytical method, namely the Kourosh method, based on the singularity perturbation method and the Liao homotopy analysis is utilized to solve the Blasius problem. In this method, an inner solution is developed in the [0,1] interval to expedite the solution convergence. The magnitude of the f ˝(0), as an essential quantity for determining the physical parameters, is directly calculated from the solution of the boundary condition problem. The advantages of this solution are that it does not need any numerical solution, it has a closed form and that its validation is shown in the entire [0,∞] interval. Furthermore, all of the desirable parameters could be extracted through a series of simple analytical operations from the final solution. This solution also satisfies the continuity conditions, which is one of the main contributions of this paper in comparison with most of the other proposed analytical solutions available in the literature. Comparison with numerical solutions reveals that the proposed method is highly accurate and convenient for application.

Keywords: Blasius equation, boundary layer, Kourosh method, analytical solution

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Authors: Y. Pala, M. O. Ertas

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In this paper, the general Riccati equation is analytically solved by a new transformation. By the method developed, looking at the transformed equation, whether or not an explicit solution can be obtained is readily determined. Since the present method does not require a proper solution for the general solution, it is especially suitable for equations whose proper solutions cannot be seen at first glance. Since the transformed second order linear equation obtained by the present transformation has the simplest form that it can have, it is immediately seen whether or not the original equation can be solved analytically. The present method is exemplified by several examples.

Keywords: Riccati equation, analytical solution, proper solution, nonlinear

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Authors: Oluwasanmi Teniola, Abraham Adeleke, Ademola Ibitoye, Moshood Shitu

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To establish an economical and efficient process for the recovery of gold metal from refractory gold ore obtained from Esperando axis of Osun state Nigeria, the adsorption of gold (III) from aqua reqia leached solution of the ore using bagasse nanoparticles has been studied under various experimental variables using batch technique. The extraction percentage of gold (III) on the prepared bagasse nanoparticles was determined from its distribution coefficients as a function of solution pH, contact time, adsorbent, adsorbate concentrations, and temperature. The rate of adsorption of gold (III) on the prepared bagasse nanoparticles is dependent on pH, metal concentration, amount of adsorbate, stirring rate, and temperature. The adsorption data obtained fit into the Langmuir and Freundlich equations. Three different temperatures were used to determine the thermodynamic parameters of the adsorption of gold (III) on bagasse nanoparticles. The heat of adsorption was measured to be a positive value ΔHo = +51.23kJ/mol, which serves as an indication that the adsorption of gold (III) on bagasse nanoparticles is endothermic. Also, the negative value of ΔGo = -0.6205 kJ/mol at 318K shows the spontaneity of the process. As the temperature was increased, the value of ΔGo becomes more negative, indicating that an increase in temperature favors the adsorption process. With the application of optimal adsorption variables, the adsorption capacity of gold was 0.78 mg/g of the adsorbent, out of which 0.70 mg of gold was desorbed with 0.1 % thiourea solution.

Keywords: adsorption, bagasse, extraction, nanoparticles, recovery

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Authors: G. V. Siva Krishna Rao, B. Srinivasa Rao

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Electrical energy is vital in every aspect of day-to-day life. Keen interest is taken on all possible sources of energy from which it can be generated and this led to the encouragement of generating electrical power using renewable energy resources such as solar, tidal waves and wind energy. Due to the increasing interest on renewable sources in recent times, the studies on integration of distributed generation to the power grid have rapidly increased. Distributed Generation (DG) is a promising solution to many power system problems such as voltage regulation, power loss and reduction in operational cost, etc. To reduce production cost, it is important to minimize the losses by determining the location and size of local generators to be placed in the radial distribution systems. In this paper, reduction of production cost by optimal size of DG unit operated at optimal power factor is dealt. The optimal size of the DG unit is calculated analytically using approximate reasoning suitable nodes and DG placement to minimize production cost with minimum loss is determined by fuzzy technique. Total Cost of Power generation is compared with and without DG unit for 1 year duration. The suggested method is programmed under MATLAB software and is tested on IEEE 33 bus system and the results are presented.

Keywords: distributed generation, operational cost, exact loss formula, optimum size, optimum location

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Authors: R. M. Chandima Ratnayake, Daniel Dyakov

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Super steel materials play vital role in construction and fabrication of structural, piping and pipeline components. They enable to minimize the life cycle costs in assuring the integrity of onshore and offshore operating systems. In this context, Duplex stainless steel (DSS) material related welding on constructions and fabrications play a significant role in maintaining and assuring integrity at an optimal expenditure over the life cycle of production and process systems as well as associated structures. In DSS welding, the factors such as gap geometry, shielding gas supply rate, welding current, and type of the welding process play a vital role on the final joint performance. Hence, an experimental investigation has been performed using engineering robust design approach (ERDA) to investigate the optimal settings that generate optimal super DSS (i.e. UNS S32750) joint performance. This manuscript illustrates the mathematical approach and experimental design, optimal parameter settings and results of verification experiment.

Keywords: duplex stainless steel welding, engineering robust design, mathematical framework, optimal parameter settings

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Authors: Qiuling Xie, Shanliang Zhu, Zongdi Sun

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In this paper, we analyzed the correlation relationship among PM2.5 from other five Air Quality Indices (AQIs) based on the grey relational degree, and built a multivariate nonlinear regression equation model of PM2.5 and the five monitoring indexes. For the optimal control problem of PM2.5, we took the partial large Cauchy distribution of membership equation as satisfaction function. We established a nonlinear programming model with the goal of maximum performance to price ratio. And the optimal control scheme is given.

Keywords: grey relational degree, multiple linear regression, membership function, nonlinear programming

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Authors: Ahmad Rouhani, Masood Jabbari, Sima Honarmand

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This paper introduces a method to optimal design of a hybrid Wind/Photovoltaic/Fuel cell generation system for a typical domestic load that is not located near the electricity grid. In this configuration the combination of a battery, an electrolyser, and a hydrogen storage tank are used as the energy storage system. The aim of this design is minimization of overall cost of generation scheme over 20 years of operation. The Matlab/Simulink is applied for choosing the appropriate structure and the optimization of system sizing. A teaching learning based optimization is used to optimize the cost function. An overall power management strategy is designed for the proposed system to manage power flows among the different energy sources and the storage unit in the system. The results have been analyzed in terms of technics and economics. The simulation results indicate that the proposed hybrid system would be a feasible solution for stand-alone applications at remote locations.

Keywords: hybrid energy system, optimum sizing, power management, TLBO

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Authors: Patrick Dzimiri

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This chapter discusses the military-orchestrated leadership change in Zimbabwe that transpired in November 2017. Fundamentally, the chapter provides a critical examination of military interference in the country's politics and its implications for a political transition in the post-Mugabe dispensation. This chapter offers insight into Zimbabwe's political crises propelled by the lack of a succession plan. It emerged that the succession battle within ZANU-PF got complicated by the militarisation of factionalism. The chapter builds from an extensive review of primary and secondary data sources on political developments before and post-Mugabe era. Vilfredo Pareto's (1848-18923) theory on elite circulation is deployed herein to explain the absence of a succession mechanism within ZANU-PF and the militarisation of socio-politics life Zimbabwe. The chapter argues that what transpired in Zimbabwe’s power wrangle within the ZANU-PF political elites was triggered by a lack of a clear succession policy. Building from insights offered by Pareto's theory of elite circulation, it is averred that the removal of Mugabe by the military did not herald any form of political transition but rather a mere power play of one elite replacing another. In addition, it is argued that the lack of political reform by the Mnangagwa government affirms the position that political elites seek power for personal self-actualisation and not the public good. The chapter concludes that Mnangagwa's rise to power is nothing but a new elite displacing the old elite structure and does not herald a positive transition and transformation in the politics of Zimbabwe.

Keywords: military, politics, zimbabwe, governance, political transition

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Authors: Ibrahim M. Elmojtaba, Rayan M. Altayeb

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Visceral leishmaniasis (VL) is a vector-borne disease caused by the protozoa parasite of the genus leishmania. The transmission of the parasite to humans and animals occurs via the bite of adult female sandflies previously infected by biting and sucking blood of an infectious humans or animals. In this paper we use a previously proposed model, and then applied two optimal controls, namely treatment and vaccination to that model to investigate optimal strategies for controlling the spread of the disease using treatment and vaccination as the system control variables. The possible impact of using combinations of the two controls, either one at a time or two at a time on the spread of the disease is also examined. Our results provide a framework for vaccination and treatment strategies to reduce susceptible and infection individuals of VL in five years.

Keywords: visceral leishmaniasis, treatment, vaccination, optimal control, numerical simulation

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Authors: Herbert W. Corley

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A scalar equilibrium (SE) is an alternative type of equilibrium in pure strategies for an n-person normal-form game G. It is defined using optimization techniques to obtain a pure strategy for each player of G by maximizing an appropriate utility function over the acceptable joint actions. The players’ actions are determined by the choice of the utility function. Such a utility function could be agreed upon by the players or chosen by an arbitrator. An SE is an equilibrium since no players of G can increase the value of this utility function by changing their strategies. SEs are formally defined, and examples are given. In a greedy SE, the goal is to assign actions to the players giving them the largest individual payoffs jointly possible. In a weighted SE, each player is assigned weights modeling the degree to which he helps every player, including himself, achieve as large a payoff as jointly possible. In a compromise SE, each player wants a fair payoff for a reasonable interpretation of fairness. In a parity SE, the players want their payoffs to be as nearly equal as jointly possible. Finally, a satisficing SE achieves a personal target payoff value for each player. The vector payoffs associated with each of these SEs are shown to be Pareto optimal among all such acceptable vectors, as well as computationally tractable.

Keywords: compromise equilibrium, greedy equilibrium, normal-form game, parity equilibrium, pure strategies, satisficing equilibrium, scalar equilibria, utility function, weighted equilibrium

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Authors: Xiaoping Qiu, Binci You, Yue Hu

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The executive time of the workflow network has an important effect on the efficiency of the business process. In this paper, the activity executive time is divided into the service time and the waiting time, then the lead time can be extracted from the waiting time. The executive time formulas of the three basic structures in the workflow network are deduced based on the activity lead time. Taken the process of e-commerce logistics as an example, insert appropriate lead time for key activities by using Petri net, and the executive time optimization model is built to minimize the waiting time with the time-cost constraints. Then the solution program-using VC++6.0 is compiled to get the optimal solution, which reduces the waiting time of key activities in the workflow, and verifies the role of lead time in the timeliness of e-commerce logistics.

Keywords: electronic business, execution time, lead time, optimization model, petri net, time workflow network

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Authors: Saeed Otarod

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In a different simple and straight forward analysis a closed-form integral solution is found for nonhomogeneous second order linear ordinary differential equations, in terms of a particular solution of their corresponding homogeneous part. To find the particular solution of the homogeneous part, the equation is transformed into a simple Riccati equation from which the general solution of non-homogeneouecond order differential equation, in the form of a closed integral equation is inferred. The method works well in manyimportant cases, such as Schrödinger equation for hydrogen-like atoms. A non-homogenous second order linear differential equation has been solved as an extra example

Keywords: explicit, linear, differential, closed form

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Authors: Badr M. Alshammari, T. Guesmi

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In recent years, the combined economic and emission power dispatch is one of the main problems of electrical power system. It aims to schedule the power generation of generators in order to minimize cost production and emission of harmful gases caused by fossil-fueled thermal units such as CO, CO₂, NO_x, and SO₂. To solve this complicated multi-objective problem, an improved version of the particle swarm optimization technique that includes non-dominated sorting concept has been proposed. Valve point loading effects and system losses have been considered. The three-unit and ten-unit benchmark systems have been used to show the effectiveness of the suggested optimization technique for solving this kind of nonconvex problem. The simulation results have been compared with those obtained using genetic algorithm based method. Comparison results show that the proposed approach can provide a higher quality solution with better performance.

Keywords: power dispatch, valve point loading effects, multiobjective optimization, Pareto solutions

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Authors: Y. Ghiassi-Farrokhfal

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The number of electric vehicles (EVs) is increasing worldwide. Replacing gas fueled cars with EVs reduces carbon emission. However, the extensive energy consumption of EVs stresses the energy systems, requiring non-green sources of energy (such as gas turbines) to compensate for the new energy demand caused by EVs in the energy systems. To make EVs even a greener solution for the future energy systems, new EV charging stations are equipped with solar PV panels and batteries. This will help serve the energy demand of EVs through the green energy of solar panels. To ensure energy availability, solar panels are combined with batteries. The energy surplus at any point is stored in batteries and is used when there is not enough solar energy to serve the demand. While EV charging stations equipped with solar panels and batteries are green and ecologically optimal, they might not be financially viable solutions, due to battery prices. To make the system viable, we should size the battery economically and operate the system optimally. This is, in general, a challenging problem because of the stochastic nature of the EV arrivals at the charging station, the available solar energy, and the battery operating system. In this work, we provide a mathematical model for this problem and we compute the return on investment (ROI) of such a system, which is designed to be ecologically and financially optimal. We also quantify the minimum required investment in terms of battery and solar panels along with the operating strategy to ensure that a charging station has enough energy to serve its EV demand at any time.

Keywords: solar energy, battery storage, electric vehicle, charging stations

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Authors: Galal H. Senussi, Muamar Benisa, Sanja Vasin

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In our business field today, one of the most important issues for any enterprises is cost minimization and profit maximization. Second issue is how to develop a strong and capable model that is able to give us desired forecasting of these two issues. Many researches deal with these issues using different methods. In this study, we developed a model for multi-criteria production program optimization, integrated with Artificial Neural Network. The prediction of the production cost and profit per unit of a product, dealing with two obverse functions at same time can be extremely difficult, especially if there is a great amount of conflict information about production parameters. Feed-Forward Neural Networks are suitable for generalization, which means that the network will generate a proper output as a result to input it has never seen. Therefore, with small set of examples the network will adjust its weight coefficients so the input will generate a proper output. This essential characteristic is of the most important abilities enabling this network to be used in variety of problems spreading from engineering to finance etc. From our results as we will see later, Feed-Forward Neural Networks has a strong ability and capability to map inputs into desired outputs.

Keywords: project profitability, multi-objective optimization, genetic algorithm, Pareto set, neural networks

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Authors: Samia Sadouki Chibani, Abdelkamel Tari

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Web service composition combines available services to provide new functionality. Given the number of available services with similar functionalities and different non functional aspects (QoS), the problem of finding a QoS-optimal web service composition is considered as an optimization problem belonging to NP-hard class. Thus, an optimal solution cannot be found by exact algorithms within a reasonable time. In this paper, a meta-heuristic bio-inspired is presented to address the QoS aware web service composition; it is based on Elephant Herding Optimization (EHO) algorithm, which is inspired by the herding behavior of elephant group. EHO is characterized by a process of dividing and combining the population to sub populations (clan); this process allows the exchange of information between local searches to move toward a global optimum. However, with Applying others evolutionary algorithms the problem of early stagnancy in a local optimum cannot be avoided. Compared with PSO, the results of experimental evaluation show that our proposition significantly outperforms the existing algorithm with better performance of the fitness value and a fast convergence.

Keywords: bio-inspired algorithms, elephant herding optimization, QoS optimization, web service composition

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Authors: Lucy Jackson, Celyn Walters, Steve Eckersley, Mini Rai, Simon Hadfield

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Space robots will play an integral part in exploring the universe and beyond. A correctly designed space robot will facilitate OOA, satellite servicing and ADR. However, problems arise when trying to design such a system as it is a highly complex multidimensional problem into which there is little research. Current design techniques are slow and specific to terrestrial manipulators. This paper presents a solution to the slow speed of robotic hardware design, and generalizes the technique to free-flying space robots. It presents Ta-DAH Design, an automated design approach that utilises a multi-objective cost function in an iterative and automated pipeline. The design approach leverages prior knowledge and facilitates the faster output of optimal designs. The result is a system that can optimise the size of the base spacecraft, manipulator and some key subsystems for any given task. Presented in this work is the methodology behind Ta-DAH Design and a number optimal space robot designs.

Keywords: space robots, automated design, on-orbit operations, hardware design

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Authors: E. Y. Jo, S. M. Park, I. S. Yeo, K. K. Kim, S. J. Park, Y. K. Kim, Y. D. Kim, C. G. Park

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SO3 is created in small quantities during the combustion of fuel that contains sulfur, with the quantity produced a function of the boiler design, fuel sulfur content, excess air level, and the presence of oxidizing agents. Typically, about 1% of the fuel sulfur will be oxidized to SO3, but it can range from 0.5% to 1.5% depending on various factors. Combustion of fuels that contain oxidizing agents, such as certain types of fuel oil or petroleum coke, can result in even higher levels of oxidation. SO3 levels in the flue gas emitted by combustion are very high, which becomes a cause of machinery corrosion or a visible blue plume. Because of that, power plants firing petroleum residues need to installation of SO3 removal system. In this study, SO3 removal system using salt solution was developed and several salts solutions were tested for obtain optimal solution for SO3 removal system. Response surface methodology was used to optimize the operation parameters such as gas-liquid ratio, concentration of salts.

Keywords: flue gas desulfurization, petroleum cokes, Sulfur trioxide, SO3 removal

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Authors: Fadzil Ahmad, Noor Ashidi Mat Isa

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This study introduces an improved genetic algorithm procedure that focuses search around near optimal solution corresponded to a group of elite chromosome. This is achieved through a novel crossover technique known as Segmented Multi Chromosome Crossover. It preserves the highly important information contained in a gene segment of elite chromosome and allows an offspring to carry information from gene segment of multiple chromosomes. In this way the algorithm has better possibility to effectively explore the solution space. The improved GA is applied for the automatic and simultaneous parameter optimization and feature selection of artificial neural network in pattern recognition of medical problem, the cancer and diabetes disease. The experimental result shows that the average classification accuracy of the cancer and diabetes dataset has improved by 0.1% and 0.3% respectively using the new algorithm.

Keywords: genetic algorithm, artificial neural network, pattern clasification, classification accuracy

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Authors: I. Goual, M. S. Goual, M. K. Gueddouda, Taïbi Saïd, Abou-Bekr Nabil, A. Ferhat

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This paper presents the study of hydro mechanical behavior of this optimal mixture. A first experimental phase was carried out in order to find the optimal mixture. This showed that the material composed of 80% tuff and 20% calcareous sand provides the maximum mechanical strength. The second experimental phase concerns the study of the drying- wetting behavior of the optimal mixture was carried out on slurry samples and compacted samples at the MPO. Experimental results let to deduce the parameters necessary for the prediction of the hydro-mechanical behavior of pavement formulated from tuff and calcareous sand mixtures, related to moisture. This optimal mixture satisfies the regulation rules and hence constitutes a good local eco-material, abundantly available, for the conception of pavements.

Keywords: tuff, sandy calcareous, road engineering, hydro mechanical behaviour, suction

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Authors: Georges Ghazi, Marc-Henry Devillers, Ruxandra M. Botez

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Aircraft flight trajectory optimization has been identified to be a promising solution for reducing both airline costs and the aviation net carbon footprint. Nowadays, this role has been mainly attributed to the flight management system. This system is an onboard multi-purpose computer responsible for providing the crew members with the optimized flight plan from a destination to the next. To accomplish this function, the flight management system uses a variety of look-up tables to compute the optimal speed and altitude for each flight regime instantly. Because the cruise is the longest segment of a typical flight, the proposed algorithm is focused on minimizing fuel consumption for this flight phase. In this paper, a complete methodology to estimate the aircraft performance and subsequently compute the optimal speed in cruise is presented. Results showed that the obtained performance database was accurate enough to predict the flight costs associated with the cruise phase.

Keywords: Cessna Citation X, cruise speed optimization, flight cost, cost index, and golden section search

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Authors: Maryam Ghoreishi, Christian Larsen

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In this paper, we investigate the effect of stochastic inputs on problem of joint optimal pricing and lot-sizing decisions where the inventory cycle is divided into advance and spot sales periods. During the advance sales period, customer can make reservations while customer with reservations can cancel their order. However, during the spot sales period customers receive the order as soon as the order is placed, but they cannot make any reservation or cancellation during that period. We assume that the inter arrival times during the advance sales and spot sales period are exponentially distributed where the arrival rate is decreasing function of price. Moreover, we assume that the number of cancelled reservations is binomially distributed. In addition, we assume that deterioration process follows an exponential distribution. We investigate two cases. First, we consider two-state case where we find the optimal price during the spot sales period and the optimal price during the advance sales period. Next, we develop a generalized case where we extend two-state case also to allow dynamic prices during the spot sales period. We apply the Markov decision theory in order to find the optimal solutions. In addition, for the generalized case, we apply the policy iteration algorithm in order to find the optimal prices, the optimal lot-size and maximum advance sales amount.

Keywords: inventory control, pricing, Markov decision theory, advance sales system

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Authors: Ali H. Daraji, Jack M. Hale, Ye Jianqiao

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With the extensive use of high specific strength structures to optimise the loading capacity and material cost in aerospace and most engineering applications, much effort has been expended to develop intelligent structures for active vibration reduction and structural health monitoring. These structures are highly flexible, inherently low internal damping and associated with large vibration and long decay time. The modification of such structures by adding lightweight piezoelectric sensors and actuators at efficient locations integrated with an optimal control scheme is considered an effective solution for structural vibration monitoring and controlling. The size and location of sensor and actuator are important research topics to investigate their effects on the level of vibration detection and reduction and the amount of energy provided by a controller. Several methodologies have been presented to determine the optimal location of a limited number of sensors and actuators for small-scale structures. However, these studies have tackled this problem directly, measuring the fitness function based on eigenvalues and eigenvectors achieved with numerous combinations of sensor/actuator pair locations and converging on an optimal set using heuristic optimisation techniques such as the genetic algorithms. This is computationally expensive for small- and large-scale structures subject to optimise a number of s/a pairs to suppress multiple vibration modes. This paper proposes an efficient method to determine optimal locations for a limited number of sensor/actuator pairs for active vibration reduction of a flexible structure based on finite element method and Hamilton’s principle. The current work takes the simplified approach of modelling a structure with sensors at all locations, subjecting it to an external force to excite the various modes of interest and noting the locations of sensors giving the largest average percentage sensors effectiveness measured by dividing all sensor output voltage over the maximum for each mode. The methodology was implemented for a cantilever plate under external force excitation to find the optimal distribution of six sensor/actuator pairs to suppress the first six modes of vibration. It is shown that the results of the optimal sensor locations give good agreement with published optimal locations, but with very much reduced computational effort and higher effectiveness. Furthermore, it is shown that collocated sensor/actuator pairs placed in these locations give very effective active vibration reduction using optimal linear quadratic control scheme.

Keywords: optimisation, plate, sensor effectiveness, vibration control

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Authors: Jiahui Yang, John Quigley, Lesley Walls

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In this paper, the authors develop a stochastic model regarding the investment in supplier delivery performance development from a buyer’s perspective. The authors propose a multivariate model through a Multinomial-Dirichlet distribution within an Empirical Bayesian inference framework, representing both the epistemic and aleatory uncertainties in deliveries. A closed form solution is obtained and the lower and upper bound for both optimal investment level and expected profit under uncertainty are derived. The theoretical properties provide decision makers with useful insights regarding supplier delivery performance improvement problems where multiple delivery statuses are involved. The authors also extend the model from a single supplier investment into a supplier portfolio, using a Lagrangian method to obtain a theoretical expression for an optimal investment level and overall expected profit. The model enables a buyer to know how the marginal expected profit/investment level of each supplier changes with respect to the budget and which supplier should be invested in when additional budget is available. An application of this model is illustrated in a simulation study. Overall, the main contribution of this study is to provide an optimal investment decision making framework for supplier development, taking into account multiple delivery statuses as well as multiple projects.

Keywords: decision making, empirical bayesian, portfolio optimization, supplier development, supply chain management

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Authors: Javad Jamali Khouei, Mohammadreza Khoshravan

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Considering that application of functionally graded material is increasing in most industries, it seems necessary to present a methodology for designing optimal profile of structures such as plate under mechanical loading which is highly consumed in industries. Therefore, volume fraction variation profile of functionally graded circular plate which has been considered two-directional is optimized so that stress of structure is minimized. For this purpose, equilibrium equations of two-directional functionally graded circular plate are solved by applying semi analytical-numerical method under mechanical loading and support conditions. By solving equilibrium equations, deflections and stresses are obtained in terms of control variables of volume fraction variation profile. As a result, the problem formula can be defined as an optimization problem by aiming at minimization of critical von-mises stress under constraints of deflections, stress and a physical constraint relating to structure of material. Then, the related problem can be solved with help of one of the metaheuristic algorithms such as genetic algorithm. Results of optimization for the applied model under constraints and loadings and boundary conditions show that functionally graded plate should be graded only in radial direction and there is no need for volume fraction variation of the constituent particles in thickness direction. For validating results, optimal values of the obtained design variables are graphically evaluated.

Keywords: two-directional functionally graded material, single objective optimization, semi analytical-numerical solution, genetic algorithm, graphical solution with contour

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Authors: A. Bari

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Integer programming is a branch of mathematical programming techniques in operations research in which some or all of the variables are required to be integer valued. Various cuts have been used to solve these problems. We have also developed cuts known as NAZ cut & A-T cut to solve the integer programming problems. These cuts are used to reduce the feasible region and then reaching the optimal solution in minimum number of steps.

Keywords: Integer Programming, NAZ cut, A-T cut, Cutting plane method

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Authors: J. F. Gonzalez-Rojo, Federico Lluesma-Rodriguez, Temoatzin Gonzalez

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Hyperloop, a new mode of transport, is gaining significance. It consists of the use of a ground-based transport system which includes a levitation system, that avoids rolling friction forces, and which has been covered with a tube, controlling the inner atmosphere lowering the aerodynamic drag forces. Thus, hyperloop is proposed as a solution to the current limitation on ground transportation. Rolling and aerodynamic problems, that limit large speeds for traditional high-speed rail or even maglev systems, are overcome using a hyperloop solution. Zeleros is one of the companies developing technology for hyperloop application worldwide. It is working on a concept that reduces the infrastructure cost and minimizes the power consumption as well as the losses associated with magnetic drag forces. For this purpose, Zeleros proposes a Hybrid ElectroMagnetic Suspension (EMS) for its prototype. In the present manuscript an active and optimal electromagnetic suspension levitation method based on nearly zero power consumption individual modules is presented. This system consists of several hybrid permanent magnet-coil levitation units that can be arranged along the vehicle. The proposed unit manages to redirect the magnetic field along a defined direction forming a magnetic circuit and minimizing the loses due to field dispersion. This is achieved using an electrical steel core. Each module can stabilize the gap distance using the coil current and either linear or non-linear control methods. The ratio between weight and levitation force for each unit is 1/10. In addition, the quotient between the lifted weight and power consumption at the target gap distance is 1/3 [kg/W]. One degree of freedom (DoF) (along the gap direction) is controlled by a single unit. However, when several units are present, a 5 DoF control (2 translational and 3 rotational) can be achieved, leading to the full attitude control of the vehicle. The proposed system has been successfully tested reaching TRL-4 in a laboratory test bench and is currently in TRL-5 state development if the module association in order to control 5 DoF is considered.

Keywords: active optimal control, electromagnetic levitation, HEMS, high-speed transport, hyperloop

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Authors: Khairul Anuar, Wai Yee Lee, Daniel C. S. Bien, Hing Wah Lee, Ishak Azid

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This paper investigates the effect of ultrasonic treatment on ZnO nutrient solution prior to the growth of ZnO nanorods, where the seed layer is annealed at 50 and 100°C. The results show that the ZnO nanorods are successfully grown on the sample annealed at 50°C in the sonicated ZnO nutrient solution with a length and a diameter of approximately 8.025 µm and 92 nm, respectively. However, no ZnO nanorods structures are observed for the sample annealed at 50°C and grown in unsonicated ZnO nutrient solution. Meanwhile, the ZnO nanorods for the sample annealed at 100°C are successfully grown in both sonicated and unsonicated ZnO nutrient solutions. The length and diameter of the nanorods for the sample grown in the sonicated solution are 8.681 µm and 1.033 nm, whereas those for the sample grown in the unsonicated solution are 7.613 µm and 1.040 nm. This result shows that with ultrasonic treatment, the length of the ZnO nanorods increases by 14%, whereas their diameter is reduced by 0.7%, resulting in an increase of aspect ratio from 7:1 to 8:1. Electroconductivity and pH sensors are used to measure the conductivity and acidity level of the sonicated and unsonicated solutions, respectively. The result shows that the conductivity increases from 87 mS/cm to 10.4 mS/cm, whereas the solution pH decreases from 6.52 to 6.13 for the sonicated and unsonicated solutions, respectively. The increase in solution conductivity and acidity level elucidates the higher amount of zinc nutrient in the sonicated solution than in the unsonicated solution.

Keywords: ultrasonic treatment, low annealing temperature, ZnO nanostructure, nanorods

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Authors: Christian Angerer, Markus Lienkamp

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Electric vehicles offer a high variety of possible drivetrain topologies with up to 4 motors. Multi-motor-designs can have several advantages regarding traction, vehicle dynamics, safety and even efficiency. With a rising number of motors, the whole drivetrain becomes more complex. All permutations of gearings, drivetrain-layouts, motor-types and –sizes lead up in a very large solution space. Single elements of this solution space can be analyzed by simulation methods. In addition to longitudinal vehicle behavior, which most optimization-approaches are restricted to, also lateral dynamics are important for vehicle dynamics, stability and efficiency. In order to compete large solution spaces and to find an optimal result, genetic algorithm based optimization is state-of-the-art. As lateral dynamics simulation is way more CPU-intensive, optimization takes much more time than in case of longitudinal-only simulation. Therefore, this paper shows an approach how to create meta-models from a 14-degree of freedom vehicle model in order to enable a numerically efficient drivetrain-layout optimization process under consideration of lateral dynamics. Different meta-modelling approaches such as neural networks or DoE are implemented and comparatively discussed.

Keywords: driving dynamics, drivetrain layout, genetic optimization, meta-modeling, lateral dynamicx

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Authors: Morteza Hadi

Abstract:

This research investigates the potential enhancement of the rollability of Cu-Ge-Ni alloy through the mitigation of microstructural and compositional inhomogeneities via two distinct heat treatment methods: homogenization and solution treatment. To achieve this objective, the alloy with the desired composition was fabricated using a vacuum arc remelting furnace (VAR), followed by sample preparation for microstructural, compositional, and heat treatment analyses at varying temperatures and durations. Characterization was conducted employing optical and scanning electron microscopy (SEM), X-ray diffraction (XRD), and Vickers hardness testing. The results obtained indicate that a minimum duration of 10 hours is necessary for adequate homogenization of the alloy at 750°C. This heat treatment effectively removes coarse dendrites from the casting microstructure and significantly reduces elemental separations. However, despite these improvements, the presence of a second phase with markedly different hardness from the matrix results in poor rolling ability for the alloy. The optimal time for solution treatment at various temperatures was determined, with the most effective cycle identified as 750°C for 2 hours, followed by rapid quenching in water. This process induces the formation of a single-phase microstructure and complete elimination of the second  phase, as confirmed by X-ray diffraction analysis. Results demonstrate a reduction in hardness by 30 Vickers, and the elimination of microstructural unevenness enables successful thickness reduction by up to 50% through rolling without encountering cracking.

Keywords: Cu-Ge-Ni alloy, homogenization. solution treatment, rollability

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