Search results for: optimal investment strategies

Authors: Afshin Jahangirzadeh, Shatirah Akib, Babak Kamali, Sadia Rahman

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Scarcity of water resources and huge costs of establishing new hydraulic installations necessitate optimal exploitation from existing reservoirs. Sustainable management and efficient exploitation from existing finite water resources are important factors in water resource management, particularly in the periods of water insufficiency and in dry regions, and on account of competitive allocations in the view of exploitation management. This study aims to minimize reservoir water release from a determined rate of demand. A numerical model for water optimal exploitation has been developed using GAMS introduced by the World Bank and applied to the case of Meijaran dam, northern Iran. The results indicate that this model can optimize the function of reservoir exploitation while required water for lower parts of the region will be supplied. Further, allocating optimal water from reservoir, the optimal rate of water allocated to any group of the users were specified to increase benefits in curve dam exploitation.

Keywords: Water resource management, water reservoirs, water allocation, GAMS, Meijaran dam

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Authors: M. S. Kelaiaia, H. Labar, S. Kelaiaia, T. Mesbah

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The development of the power electronics has allowed increasing the precision and reliability of the electrical devices, thanks to the adjustable inverters, as the Pulse Wide Modulation (PWM) applied to the three level inverters, which is the object of this study. The authors treat the relation between the law order adopted for a given system and the oscillations of the electrical and mechanical parameters of which the tolerance depends on the process with which they are integrated (paper factory, lifting of the heavy loads, etc.).Thus, the best choice of the regulation indexes allows us to achieve stability and safety training without investment (management of existing equipment). The optimal behavior of any electric device can be achieved by the minimization of the stored electrical and mechanical energy.

Keywords: Multi level inverter, PWM, Harmonics, oscillation, control.

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Authors: Nhien-An Le-Khac, Sammer Markos, M-Tahar Kechadi

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Today, money laundering (ML) poses a serious threat not only to financial institutions but also to the nation. This criminal activity is becoming more and more sophisticated and seems to have moved from the cliché of drug trafficking to financing terrorism and surely not forgetting personal gain. Most international financial institutions have been implementing anti-money laundering solutions (AML) to fight investment fraud. However, traditional investigative techniques consume numerous man-hours. Recently, data mining approaches have been developed and are considered as well-suited techniques for detecting ML activities. Within the scope of a collaboration project for the purpose of developing a new solution for the AML Units in an international investment bank, we proposed a data mining-based solution for AML. In this paper, we present a heuristics approach to improve the performance for this solution. We also show some preliminary results associated with this method on analysing transaction datasets.

Keywords: data mining, anti money laundering, clustering, heuristics.

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Authors: Ammar Redza Ahmad Rizal, Shahrina Md Nordin, Mohd Shamsuri Saad, Kamariah Ismail

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Communication is becoming a significant tool to engage stakeholders since half of the century ago. In the recent years, there has been rapid growth of new technology developments. In tandem with such developments, there has been growing emphasis in communication strategies and management especially in determining the level of influence and management strategies among the said stakeholders on particular field. This paper presents a research conceptual framework focusing on stakeholder theories, communication and management strategies to be implied on the engagement of stakeholders of new technology developments of fertilizer industry in Malaysia. Framework espoused in this paper will provide insights into the various stakeholder theories and engagement strategies from different principal necessary for a successful introduction of new technology development in the above stated industry. The proposed framework has theoretical significance in filling the gap of the body of knowledge in the implementation of communication strategies in Malaysian fertilizer industry.

Keywords: Communication Strategies, Fertilizer Industry, New Technology Development, Stakeholders Management.

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Authors: Mohamed Shawki Elamir, Heinrich Gotzig, Raoul Zoellner, Patrick Maeder

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In this work, a methodology is presented for identifying the optimal digitization parameters for the analog signal of ultrasonic sensors. These digitization parameters are the resolution of the analog to digital conversion and the sampling rate. This is accomplished though the derivation of characteristic curves based on Fano inequality and the calculation of the mutual information content over a given dataset. The mutual information is calculated between the examples in the dataset and the corresponding variation in the feature that needs to be estimated. The optimal parameters are identified in a manner that ensures optimal estimation performance while preventing inefficiency in using unnecessarily powerful analog to digital converters.

Keywords: Analog to digital conversion, digitization, sampling rate, ultrasonic sensors.

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Authors: H. 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: S. M. Seyedhosseini, A. Makui, M. Ghadami

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Globalization and therefore increasing tight competition among companies, have resulted to increase the importance of making well-timed decision. Devising and employing effective strategies, that are flexible and adaptive to changing market, stand a greater chance of being effective in the long-term. In other side, a clear focus on managing the entire product lifecycle has emerged as critical areas for investment. Therefore, applying wellorganized tools to employ past experience in new case, helps to make proper and managerial decisions. Case based reasoning (CBR) is based on a means of solving a new problem by using or adapting solutions to old problems. In this paper, an adapted CBR model with k-nearest neighbor (K-NN) is employed to provide suggestions for better decision making which are adopted for a given product in the middle of life phase. The set of solutions are weighted by CBR in the principle of group decision making. Wrapper approach of genetic algorithm is employed to generate optimal feature subsets. The dataset of the department store, including various products which are collected among two years, have been used. K-fold approach is used to evaluate the classification accuracy rate. Empirical results are compared with classical case based reasoning algorithm which has no special process for feature selection, CBR-PCA algorithm based on filter approach feature selection, and Artificial Neural Network. The results indicate that the predictive performance of the model, compare with two CBR algorithms, in specific case is more effective.

Keywords: Case based reasoning, Genetic algorithm, Groupdecision making, Product management.

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Authors: R. M. Chandima Ratnayake, Daniel Dyakov

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Super steel materials play a vital role in the construction and fabrication of structural, piping and pipeline components. In assuring the integrity of onshore and offshore operating systems, they enable life cycle costs to be minimized. In this context, Duplex stainless steel (DSS) material related welding on constructions and fabrications plays 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, factors such as gap geometry, shielding gas supply rate, welding current, and type of the welding process are vital to the final joint performance. Hence, an experimental investigation has been performed using an 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 the verification experiment.

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

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Authors: Yuekun Chen, Yousef Sardahi, Salam Hajjar, Christopher Greer

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This paper presents a multi-objective optimal design of a cascade control system for an underactuated mechanical system. Cascade control structures usually include two control algorithms (inner and outer). To design such a control system properly, the following conflicting objectives should be considered at the same time: 1) the inner closed-loop control must be faster than the outer one, 2) the inner loop should fast reject any disturbance and prevent it from propagating to the outer loop, 3) the controlled system should be insensitive to measurement noise, and 4) the controlled system should be driven by optimal energy. Such a control problem can be formulated as a multi-objective optimization problem such that the optimal trade-offs among these design goals are found. To authors best knowledge, such a problem has not been studied in multi-objective settings so far. In this work, an underactuated mechanical system consisting of a rotary servo motor and a ball and beam is used for the computer simulations, the setup parameters of the inner and outer control systems are tuned by NSGA-II (Non-dominated Sorting Genetic Algorithm), and the dominancy concept is used to find the optimal design points. The solution of this problem is not a single optimal cascade control, but rather a set of optimal cascade controllers (called Pareto set) which represent the optimal trade-offs among the selected design criteria. The function evaluation of the Pareto set is called the Pareto front. The solution set is introduced to the decision-maker who can choose any point to implement. The simulation results in terms of Pareto front and time responses to external signals show the competing nature among the design objectives. The presented study may become the basis for multi-objective optimal design of multi-loop control systems.

Keywords: Cascade control, multi-loop control systems, multi-objective optimization, optimal control.

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Authors: Grace Adebisi Fayombo

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This study investigated the relationships between the active learning strategies (discussion, video clips, game show, role– play, five minute paper, clarification pauses, and small group) and academic achievement among a sample of 158 undergraduate psychology students in The University of the West Indies (UWI), Barbados. Results revealed statistically significant positive correlations between active learning strategies and students’ academic achievement; so also the active learning strategies contributed 22% (Rsq=0.222) to the variance being accounted for in academic achievement and this was found to be statistically significant (F(7,150) = 6.12, p < .05). Additionally, group work emerged as the best active learning strategy and had the highest correlation with the students’ academic achievement. These results were discussed in the light of the importance of the active learning strategies promoting academic achievement among the university students.

Keywords: Academic achievement, active learning strategies, psychology, undergraduates.

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Authors: Chioma Ifeoma Agbasimelo, Stephen Afam Kenechukwu

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The study examined consumers’ responses to non-traditional marketing communication strategies in advertising herbal products. The study identified the following non-traditional marketing communication strategies: (a) trado-instrumental marketing strategy, (b) trado-demonstrative marketing strategy, and (c) trado-iconographic marketing strategy. Anchored on the Black Box Theory, it adopted the survey design of three metropolises (Awka, Onitsha, and Nnewi) in Anambra State, Nigeria. Major findings indicated that among the identified strategies, the trado-instrumental marketing strategy is the most dominant strategy. Other strategies: (b) trado-demonstrative marketing strategy and (c) trado-iconographic marketing strategy, are sparingly used in semi-urban cities. It also found that consumers’ preferences and adoption of non-traditional marketing communication were minimal. Based on the findings, there is a need to create a unified system of integration of both traditional and non-traditional marketing communication strategies due to technology interfaces.

Keywords: Advertising, consumers’ responses, herbal products, non-traditional marketing communication strategies.

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Authors: Shyam S.N. Perera

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The optimal control problem for the viscoelastic melt spinning process has not been reported yet in the literature. In this study, an optimal control problem for a mathematical model of a viscoelastic melt spinning process is considered. Maxwell-Oldroyd model is used to describe the rheology of the polymeric material, the fiber is made of. The extrusion velocity of the polymer at the spinneret as well as the velocity and the temperature of the quench air and the fiber length serve as control variables. A constrained optimization problem is derived and the first–order optimality system is set up to obtain the adjoint equations. Numerical solutions are carried out using a steepest descent algorithm. A computer program in MATLAB is developed for simulations.

Keywords: Fiber spinning, Maxwell-Oldroyd, Optimal control, First-order optimality system, Adjoint system

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Authors: B. Marasović, S. Pivac, S. V. Vukasović

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Constructing a portfolio of investments is one of the most significant financial decisions facing individuals and institutions. In accordance with the modern portfolio theory maximization of return at minimal risk should be the investment goal of any successful investor. In addition, the costs incurred when setting up a new portfolio or rebalancing an existing portfolio must be included in any realistic analysis. In this paper rebalancing an investment portfolio in the presence of transaction costs on the Croatian capital market is analyzed. The model applied in the paper is an extension of the standard portfolio mean-variance optimization model in which transaction costs are incurred to rebalance an investment portfolio. This model allows different costs for different securities, and different costs for buying and selling. In order to find efficient portfolio, using this model, first, the solution of quadratic programming problem of similar size to the Markowitz model, and then the solution of a linear programming problem have to be found. Furthermore, in the paper the impact of transaction costs on the efficient frontier is investigated. Moreover, it is shown that global minimum variance portfolio on the efficient frontier always has the same level of the risk regardless of the amount of transaction costs. Although efficient frontier position depends of both transaction costs amount and initial portfolio it can be concluded that extreme right portfolio on the efficient frontier always contains only one stock with the highest expected return and the highest risk.

Keywords: Croatian capital market, Fractional quadratic programming, Markowitz model, Portfolio optimization, Transaction costs.

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Authors: Muhammad Sohail Khan, Rehan Ali Shah

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The present paper applies the optimal homotopy perturbation method (OHPM) and the optimal homotopy asymptotic method (OHAM) introduced recently to obtain analytic approximations of the non-linear equations modeling the flow of polymer in case of wire coating of a corotational Maxwell fluid. Expression for the velocity field is obtained in non-dimensional form. Comparison of the results obtained by the two methods at different values of non-dimensional parameter l₁₀, reveal that the OHPM is more effective and easy to use. The OHPM solution can be improved even working in the same order of approximation depends on the choices of the auxiliary functions.

Keywords: Wire coating die, Corotational Maxwell model, optimal homotopy asymptotic method, optimal homotopy perturbation method.

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Authors: P. Georgieva, S. Feyo de Azevedo

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This paper is focused on issues of process modeling and two model based control strategies of a fed-batch sugar crystallization process applying the concept of artificial neural networks (ANNs). The control objective is to force the operation into following optimal supersaturation trajectory. It is achieved by manipulating the feed flow rate of sugar liquor/syrup, considered as the control input. The control task is rather challenging due to the strong nonlinearity of the process dynamics and variations in the crystallization kinetics. Two control alternatives are considered – model predictive control (MPC) and feedback linearizing control (FLC). Adequate ANN process models are first built as part of the controller structures. MPC algorithm outperforms the FLC approach with respect to satisfactory reference tracking and smooth control action. However, the MPC is computationally much more involved since it requires an online numerical optimization, while for the FLC an analytical control solution was determined.

Keywords: artificial neural networks, nonlinear model control, process identification, crystallization process

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Authors: R. Rajabpour, N. Talebbeydokhti, M. H. Ahmadi

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In recent years, new techniques for solving complex problems in engineering are proposed. One of these techniques is JPSO algorithm. With innovative changes in the nature of the jump algorithm JPSO, it is possible to construct a graph-based solution with a new algorithm called G-JPSO. In this paper, a new algorithm to solve the optimal control problem Fletcher-Powell and optimal control of pumps in water distribution network was evaluated. Optimal control of pumps comprise of optimum timetable operation (status on and off) for each of the pumps at the desired time interval. Maximum number of status on and off for each pumps imposed to the objective function as another constraint. To determine the optimal operation of pumps, a model-based optimization-simulation algorithm was developed based on G-JPSO and JPSO algorithms. The proposed algorithm results were compared well with the ant colony algorithm, genetic and JPSO results. This shows the robustness of proposed algorithm in finding near optimum solutions with reasonable computational cost.

Keywords: G-JPSO, operation, optimization, pumping station, water distribution networks.

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Authors: Nur Atiqah Rochin Demong, Jie Lu, Farookh Khadeer Hussain

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Property investment in the real estate industry has a high risk due to the uncertainty factors that will affect the decisions made and high cost. Analytic hierarchy process has existed for some time in which referred to an expert-s opinion to measure the uncertainty of the risk factors for the risk analysis. Therefore, different level of experts- experiences will create different opinion and lead to the conflict among the experts in the field. The objective of this paper is to propose a new technique to measure the uncertainty of the risk factors based on multidimensional data model and data mining techniques as deterministic approach. The propose technique consist of a basic framework which includes four modules: user, technology, end-user access tools and applications. The property investment risk analysis defines as a micro level analysis as the features of the property will be considered in the analysis in this paper.

Keywords: Uncertainty factors, data mining, multidimensional data model, risk analysis.

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Authors: Aniruddha Bhattacharya, Pranab Kumar Chattopadhyay

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Optimal reactive power flow is an optimization problem with one or more objective of minimizing the active power losses for fixed generation schedule. The control variables are generator bus voltages, transformer tap settings and reactive power output of the compensating devices placed on different bus bars. Biogeography- Based Optimization (BBO) technique has been applied to solve different kinds of optimal reactive power flow problems subject to operational constraints like power balance constraint, line flow and bus voltages limits etc. BBO searches for the global optimum mainly through two steps: Migration and Mutation. In the present work, BBO has been applied to solve the optimal reactive power flow problems on IEEE 30-bus and standard IEEE 57-bus power systems for minimization of active power loss. The superiority of the proposed method has been demonstrated. Considering the quality of the solution obtained, the proposed method seems to be a promising one for solving these problems.

Keywords: Active Power Loss, Biogeography-Based Optimization, Migration, Mutation, Optimal Reactive Power Flow.

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Authors: R. B. Mishra

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Hidden Markov Model (HMM) has been used in prediction and determination of states that generate different neural activations as well as mental working conditions. This paper addresses two applications of HMM; one to determine the optimal sequence of states for two neural states: Active (AC) and Inactive (IA) for the three emission (observations) which are for No Working (NW), Waiting (WT) and Working (W) conditions of human beings. Another is for the determination of optimal sequence of intentionality i.e. Believe (B), Desire (D), and Intention (I) as the states and three observational sequences: NW, WT and W. The computational results are encouraging and useful.

Keywords: BDI, HMM, neural activation, optimal states, working conditions.

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Authors: Mouataz Zreika, Maria Estela Varua

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Stock investment decisions are often made based on current events of the global economy and the analysis of historical data. Conversely, visual representation could assist investors’ gain deeper understanding and better insight on stock market trends more efficiently. The trend analysis is based on long-term data collection. The study adopts a hybrid method that combines the Clustering algorithm and Force-directed algorithm to overcome the scalability problem when visualizing large data. This method exemplifies the potential relationships between each stock, as well as determining the degree of strength and connectivity, which will provide investors another understanding of the stock relationship for reference. Information derived from visualization will also help them make an informed decision. The results of the experiments show that the proposed method is able to produced visualized data aesthetically by providing clearer views for connectivity and edge weights.

Keywords: Clustering, force-directed, graph drawing, stock investment analysis.

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Authors: F. Di Pillo, G. Capece, L. Cricelli, N. Levialdi

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The liberalization and privatization processes have forced public utility companies to face new competitive challenges, implementing strategies to gain market share and, at the same time, keep the old customers. To this end, many companies have carried out mergers, acquisitions and conglomerations in order to diversify their business. This paper focuses on companies operating in the free energy market in Italy. In the last decade, this sector has undergone profound changes that have radically changed the competitive scenario and have led companies to implement diversification strategies of the business. Our work aims to evaluate the economic and financial performances obtained by energy companies, following the beginning of the liberalization process, verifying the possible relationship with the implemented diversification strategies.

Keywords: Business diversification strategies, M&A, the Italian energy market liberalization, economic and financial performances.

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Authors: Byung Hoon Seo, Hyun Gyu Kim, Tae Won Seo

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Stair climbing is one of critical issues for field robots to widen applicable areas. This paper presents optimal design on kinematic parameters of a new robotic platform for stair climbing. The robotic platform climbs various stairs by body flip locomotion with caterpillar type main platform. Kinematic parameters such as platform length, platform height, and caterpillar rotation speed are optimized to maximize stair climbing stability. Three types of stairs are used to simulate typical user conditions. The optimal design process is conducted based on Taguchi methodology, and resulting parameters with optimized objective function are presented. In near future, a prototype is assembled for real environment testing.

Keywords: Stair climbing robot, Optimal design, Taguchi methodology, Caterpillar, Kinematic parameters.

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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: Yongsheng Guo, Mirza Muhammad Naseer, Xiaoxian Zhu

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This study explores the perceptions and conducts of Chinese foreign direct investment (FDI) in Africa from ethical and cultural perspectives. It offers a better understanding of how ethical and cultural factors affect Chinese investment in Africa and how the investment projects performed in Africa from both Chinese investors and African stakeholders’ perceptions. It adopted a grounded theory approach and conducted 30 in-depth interviews with corporate managers. Grounded theory models are developed to link the ethical and cultural factors, actions, and consequences. Results reveal that some ethical concepts like the unity of humans and nature, benevolence, virtue and responsibility, and cultural traits including propriety, righteousness, sincerity, equilibrium, long-term orientation, and principles affect Chinese investors when making investments in Africa. Most Chinese investors harmonize with local managers, cooperate with each other, and are gentle and courteous to partners. They take stable and steady actions and invest in infrastructure and agriculture projects and adopt a virtue governance system in the organization. This study finds that consequently, Chinese investors and local partners take complementary advantages, make achievements sequentially, and therefore both sides can win. They recognize great potentials and make sustainable development in Africa to achieve the Great Together in the future. This study proposes a Chinese ethics and governance system including economic, social, and political perspectives and compares it with alternative systems. It makes implications to the world island theory and propose suggestions to solve the Clash of Civilizations problem.

Keywords: Foreign Direct Investment, Ethics, National Culture, China, Africa.

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Authors: Carol Anne Hargreaves

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A key issue in stock investment is how to select representative features for stock selection. The objective of this paper is to firstly determine whether an automated stock investment system, using machine learning techniques, may be used to identify a portfolio of growth stocks that are highly likely to provide returns better than the stock market index. The second objective is to identify the technical features that best characterize whether a stock’s price is likely to go up and to identify the most important factors and their contribution to predicting the likelihood of the stock price going up. Unsupervised machine learning techniques, such as cluster analysis, were applied to the stock data to identify a cluster of stocks that was likely to go up in price – portfolio 1. Next, the principal component analysis technique was used to select stocks that were rated high on component one and component two – portfolio 2. Thirdly, a supervised machine learning technique, the logistic regression method, was used to select stocks with a high probability of their price going up – portfolio 3. The predictive models were validated with metrics such as, sensitivity (recall), specificity and overall accuracy for all models. All accuracy measures were above 70%. All portfolios outperformed the market by more than eight times. The top three stocks were selected for each of the three stock portfolios and traded in the market for one month. After one month the return for each stock portfolio was computed and compared with the stock market index returns. The returns for all three stock portfolios was 23.87% for the principal component analysis stock portfolio, 11.65% for the logistic regression portfolio and 8.88% for the K-means cluster portfolio while the stock market performance was 0.38%. This study confirms that an automated stock investment system using machine learning techniques can identify top performing stock portfolios that outperform the stock market.

Keywords: Machine learning, stock market trading, logistic principal component analysis, automated stock investment system.

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Authors: M Ahmadigorji, A. Abbaspour, A Rajabi-Ghahnavieh, M. Fotuhi- Firuzabad

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DG application has received increasing attention during recent years. The impact of DG on various aspects of distribution system operation, such as reliability and energy loss, depend highly on DG location in distribution feeder. Optimal DG placement is an important subject which has not been fully discussed yet. This paper presents an optimization method to determine optimal DG placement, based on a cost/worth analysis approach. This method considers technical and economical factors such as energy loss, load point reliability indices and DG costs, and particularly, portability of DG. The proposed method is applied to a test system and the impacts of different parameters such as load growth rate and load forecast uncertainty (LFU) on optimum DG location are studied.

Keywords: Distributed generation, optimal placement, cost/worthanalysis, customer interruption cost, Dynamic programming

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Authors: Pei-Hsing Huang, Wei-Ju Huang

Abstract:

Investment casting is commonly used in the production of metallic components with complex shapes, due to its high dimensional precision, good surface finish, and low cost. However, the process is cumbersome, and the period between trial casting and final production can be very long, thereby limiting business opportunities and competitiveness. In this study, we replaced conventional wax injection with stereolithography (SLA) 3D printing to speed up the trial process and reduce costs. We also used silicone molds to further reduce costs to avoid the high costs imposed by photosensitive resin.

Keywords: Investment casting, stereolithography, wax molding, 3D printing.

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Authors: Hitoshi Takata, Tomohiro Hachino, Masaki Horai, Kazuo Komatsu

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In this paper, we are concerned with the design and its simulation studies of a modified extremum seeking control for nonlinear systems. A standard extremum seeking control has a simple structure, but it takes a long time to reach an optimal operating point. We consider a modification of the standard extremum seeking control which is aimed to reach the optimal operating point more speedily than the standard one. In the modification, PD acceleration term is added before an integrator making a principal control, so that it enables the objects to be regulated to the optimal point smoothly. This proposed method is applied to Monod and Williams-Otto models to investigate its effectiveness. Numerical simulation results show that this modified method can improve the time response to the optimal operating point more speedily than the standard one.

Keywords: Extremum seeking control, Monod model, Williams- Otto model, PD acceleration term, Optimal operating point.

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Authors: Shyam S.N. Perera

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An optimal control problem for a mathematical model of efficiency of antiviral therapy in hepatitis B virus infections is considered. The aim of the study is to control the new viral production, block the new infection cells and maintain the number of uninfected cells in the given range. The optimal controls represent the efficiency of antiviral therapy in inhibiting viral production and preventing new infections. Defining the cost functional, the optimal control problem is converted into the constrained optimization problem and the first order optimality system is derived. For the numerical simulation, we propose the steepest descent algorithm based on the adjoint variable method. A computer program in MATLAB is developed for the numerical simulations.

Keywords: Virus infection model, Optimal control, Adjoint system, Steepest descent

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Authors: Michael Todinov, Eberechi Weli

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The paper suggests for the first time the use of dynamic programming techniques for optimal risk reduction in the railway industry. It is shown that by using the concept ‘amount of removed risk by a risk reduction option’, the problem related to optimal allocation of a fixed budget to achieve a maximum risk reduction in the railway industry can be reduced to an optimisation problem from dynamic programming. For n risk reduction options and size of the available risk reduction budget B (expressed as integer number), the worst-case running time of the proposed algorithm is O (n x (B+1)), which makes the proposed method a very efficient tool for solving the optimal risk reduction problem in the railway industry. 

Keywords: Optimisation, railway risk reduction, budget constraints, dynamic programming.

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