Search results for: Pareto optimal; Stakeholder preference

Authors: Yael Dubinsky, Orit Hazzan

Abstract:

There is a constant need for hi-tech innovation to be decentralized to peripheral regions. This work describes how we applied Design Science Research (DSR) principles to define what we refer to as the Sea of Galilee (SoG) method. The goal of the SoG method is to harness existing and new technological initiatives in peripheral regions to create a socio-technological network that can initiate and maintain hi-tech activities. The SoG method consists of a set of principles, a stakeholder network, and actual hi-tech business initiatives, including their infrastructure and practices. The three cycles of DSR, the Relevance, Design, and Rigor cycles, lay out a research framework to sharpen the requirements, collect data from case studies, and iteratively refine the SoG method based on the existing knowledge base. We propose that the SoG method can be deployed by regional authorities that wish to be considered as smart regions (an extension of the notion of smart cities).

Keywords: Design Science Research, socio-technological initiatives, Sea of Galilee method, periphery stakeholder network, hi-tech initiatives.

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Authors: Ziquan Hu, Kun She, Shahzad Ali, Kai Yan

Abstract:

Game theory could be used to analyze the conflicted issues in the field of information hiding. In this paper, 2-phase game can be used to build the embedder-attacker system to analyze the limits of hiding capacity of embedding algorithms: the embedder minimizes the expected damage and the attacker maximizes it. In the system, the embedder first consumes its resource to build embedded units (EU) and insert the secret information into EU. Then the attacker distributes its resource evenly to the attacked EU. The expected equilibrium damage, which is maximum damage in value from the point of view of the attacker and minimum from the embedder against the attacker, is evaluated by the case when the attacker attacks a subset from all the EU. Furthermore, the optimal equilibrium capacity of hiding information is calculated through the optimal number of EU with the embedded secret information. Finally, illustrative examples of the optimal equilibrium capacity are presented.

Keywords: 2-Phase Game, Expected Equilibrium damage, InformationHiding, Optimal Equilibrium Capacity.

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

Abstract:

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: Haifeng Wang, Haili Zhang

Abstract:

Most movie recommendation systems have been developed for customers to find items of interest. This work introduces a predictive model usable by small and medium-sized enterprises (SMEs) who are in need of a data-based and analytical approach to stock proper movies for local audiences and retain more customers. We used classification models to extract features from thousands of customers’ demographic, behavioral and social information to predict their movie genre preference. In the implementation, a Gaussian kernel support vector machine (SVM) classification model and a logistic regression model were established to extract features from sample data and their test error-in-sample were compared. Comparison of error-out-sample was also made under different Vapnik–Chervonenkis (VC) dimensions in the machine learning algorithm to find and prevent overfitting. Gaussian kernel SVM prediction model can correctly predict movie genre preferences in 85% of positive cases. The accuracy of the algorithm increased to 93% with a smaller VC dimension and less overfitting. These findings advance our understanding of how to use machine learning approach to predict customers’ preferences with a small data set and design prediction tools for these enterprises.

Keywords: Computational social science, movie preference, machine learning, SVM.

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

Abstract:

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: M. R. Alrashidi, M. E. El-Hawary

Abstract:

Environmental awareness and the recent environmental policies have forced many electric utilities to restructure their operational practices to account for their emission impacts. One way to accomplish this is by reformulating the traditional economic dispatch problem such that emission effects are included in the mathematical model. This paper presents a Particle Swarm Optimization (PSO) algorithm to solve the Economic- Emission Dispatch problem (EED) which gained recent attention due to the deregulation of the power industry and strict environmental regulations. The problem is formulated as a multi-objective one with two competing functions, namely economic cost and emission functions, subject to different constraints. The inequality constraints considered are the generating unit capacity limits while the equality constraint is generation-demand balance. A novel equality constraint handling mechanism is proposed in this paper. PSO algorithm is tested on a 30-bus standard test system. Results obtained show that PSO algorithm has a great potential in handling multi-objective optimization problems and is capable of capturing Pareto optimal solution set under different loading conditions.

Keywords: Economic emission dispatch, economic cost dispatch, particle swarm, multi-objective optimization.

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Authors: Kapse Swapnil, K. Shankar

Abstract:

Aiming at optimizing the weight and deflection of cantilever beam subjected to maximum stress and maximum deflection, Multi-objective Particle Swarm Optimization (MOPSO) with Utopia Point based local search is implemented. Utopia point is used to govern the search towards the Pareto Optimal set. The elite candidates obtained during the iterations are stored in an archive according to non-dominated sorting and also the archive is truncated based on least crowding distance. Local search is also performed on elite candidates and the most diverse particle is selected as the global best. This method is implemented on standard test functions and it is observed that the improved algorithm gives better convergence and diversity as compared to NSGA-II in fewer iterations. Implementation on practical structural problem shows that in 5 to 6 iterations, the improved algorithm converges with better diversity as evident by the improvement of cantilever beam on an average of 0.78% and 9.28% in the weight and deflection respectively compared to NSGA-II.

Keywords: Utopia point, multi-objective particle swarm optimization, local search, cantilever beam.

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Authors: R. M. Chandima Ratnayake, Daniel Dyakov

Abstract:

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: Elif Alaybeyoğlu, Y. Esra Albayrak

Abstract:

Marketing establishes a communication network between producers and consumers. Nowadays, marketing approach is customer-focused and products are directly oriented to meet customer needs. Marketing, which is a long process, needs organization and management. Therefore strategic marketing planning becomes more and more important in today’s competitive conditions. Main focus of this paper is to evaluate pricing strategies and select the best pricing strategy solution while considering internal and external factors influencing the company’s pricing decisions associated with new product development. To reflect the decision maker’s subjective preference information and to determine the weight vector of factors (attributes), the fuzzy linear programming technique for multidimensional analysis of preference (LINMAP) under intuitionistic fuzzy (IF) environments is used.

Keywords: IF Sets, LINMAP, MAGDM, Marketing.

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Authors: C. Ardil

Abstract:

This paper presents a multiple criteria decision making analysis technique for selecting fighter aircraft for the national air force. The selection of military aircraft is a process consisting of contradictory goals and objectives. When a modern air force needs to choose fighter aircraft to upgrade existing fleets, a multiple criteria decision making analysis and scenario planning for defense acquisition has been put forward. The selection of fighter aircraft for the air defense force is a strategic decision making process, since the purchase or lease of fighter jets, maintenance and operating costs and having a fleet is the biggest cost for the air force. Multiple criteria decision making analysis methods are effectively applied to facilitate decision making from various available options. The selection criteria were determined using the literature on the problem of fighter aircraft selection. The selection of fighter aircraft to be purchased for the air defense forces is handled using a multiple criteria decision making analysis technique that also determines a suitable methodological approach for the defense procurement and fleet upgrade planning process. The aim of this study is to originate an approach to evaluate fighter aircraft alternatives, Su-35, F-35, and TF-X (MMU), based on technique for order preference by similarity to ideal solution (TOPSIS).

Keywords: Fighter Aircraft, Fighter Aircraft Selection, Technique for Order Preference by Similarity to Ideal Solution, TOPSIS, Multiple Criteria Decision Making, Multiple Criteria Decision Making Analysis, MCDMA, Su-35, F-35, TF-X (MMU)

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Authors: Asaiel Alohaly

Abstract:

A theoretical framework for corporate governance is needed to bridge the gap between the corporate governance of private companies and State-Owned Enterprises (SOEs). The two dominant models, being shareholder and stakeholder, do not always address the specific requirements and challenges posed by ‘hybrid’ companies; namely, previously national bodies that have been privatised while the government retains significant control or holds a majority of shares. Thus, an exploratory theoretical study is needed to identify how ‘hybrid’ companies should be defined and why the state model should be acknowledged since it is the less conspicuous model in comparison with the shareholder and stakeholder models. This research focuses on the state model of corporate governance to understand the complex ownership, control pattern, goals, and corporate governance of these hybrid companies. The significance of this research lies in the fact that there is a limited available publication on the state model. This research argues for the state model, which proceeds from an understanding of the institutionally embedded characteristics of hybrid companies, where the government as a shareholder, is either a majority of the total shares, or has been granted power based on the rule of law; the company bylaws.

Keywords: Corporate governance, control, shareholders, state model.

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Authors: Tao Yin, Zeqiang Zhang, Wei Liang, Yanqing Zeng, Yu Zhang

Abstract:

To accelerate the remanufacturing process of electronic waste products, this study designs a partial disassembly line with the multi-robotic station to effectively dispose of excessive wastes. The multi-robotic partial disassembly line is a technical upgrade to the existing manual disassembly line. Balancing optimization can make the disassembly line smoother and more efficient. For partial disassembly line balancing with the multi-robotic station (PDLBMRS), a mixed-integer programming model (MIPM) considering the robotic efficiency differences is established to minimize cycle time, energy consumption and hazard index and to calculate their optimal global values. Besides, an enhanced NSGA-II algorithm (HNSGA-II) is proposed to optimize PDLBMRS efficiently. Finally, MIPM and HNSGA-II are applied to an actual mixed disassembly case of two types of computers, the comparison of the results solved by GUROBI and HNSGA-II verifies the correctness of the model and excellent performance of the algorithm, and the obtained Pareto solution set provides multiple options for decision-makers.

Keywords: Waste disposal, disassembly line balancing, multi-robot station, robotic efficiency difference, HNSGA-II.

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Authors: Shyam S.N. Perera

Abstract:

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: Muhammad Sohail Khan, Rehan Ali Shah

Abstract:

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

Abstract:

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: Charalampos Saridakis, Stelios Tsafarakis

Abstract:

Although environmental concern is on the rise across Europe, current market data indicate that adoption rates of environmentally friendly vehicles remain extremely low. Against this background, the aim of this paper is to a) assess preferences of European consumers for clean-fuel cars and their characteristics and b) design car lines that optimize the combination of fuel types among models in the line-up. In this direction, the authors introduce a new evolutionary mechanism and implement it to stated-preference data derived from a large-scale choice-based conjoint experiment that measures consumer preferences for various factors affecting clean-fuel vehicle (CFV) adoption. The proposed two-step methodology provides interesting insights into how new and existing fuel-types can be combined in a car line that maximizes customer satisfaction.

Keywords: Clean-fuel vehicles, product line design, conjoint analysis, choice experiment, differential evolution.

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Authors: Aniruddha Bhattacharya, Pranab Kumar Chattopadhyay

Abstract:

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

Abstract:

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: C. Ardil

Abstract:

This paper presents a multiple criteria evaluation analysis for airline quality rating using the preference analysis for reference ideal solution (PARIS) and the technique for order of preference by similarity to ideal solution (TOPSIS) approaches. The airline quality rating was developed as an objective method for assessing airline quality on combined multiple performance criteria and the importance weights of criteria. The selected multiple performance criteria were determined as on-time arrivals, mishandled baggage, involuntary denied boardings, and consumer complaints. The multiple criteria decision making analysis results show that the alternative ( a2) airline is the best-rated airline.

Keywords: airline quality rating, multiple criteria decision making, multiple criteria decision making analysis, entropy weight, MCDMA, PARIS, TOPSIS

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Authors: Ashiquer Rahman

Abstract:

The cutting edge knowledge mediation system called ‘ePLANETe’ provides a framework for building knowledge, tools, and methods for education, research, and sustainable practices, as well as the deliberative assessment support for Higher Education, Research Institutions, and elsewhere e.g., the collaborative learning and research on sustainability and biodiversity issues of territorial development sectors. The paper is to present the analytical perspective of the ‘ePLANETe’ concept and functionalities as an experimental platform for contributing to sustainability assessment. Now the ‘ePLANETe’ can be seen as experimentation of the challenges of “ICT for Green”. The digital technologies of ‘ePLANETe’ are exploited (i) to facilitate collaborative research, learning tools, and knowledge for sustainability challenges, and (ii) as deliberation support tools in pursuing of sustainability performance and practices in territorial governance, public policy, and business strategy, as well as in the higher education sectors itself. The paper investigates the dealing capacity of qualitative and quantitative assessment of agriculture sustainability through the stakeholder-based integrated assessment. Specifically, this paper focuses on integrating system methodologies with Deliberation Support Tools (DST) and INTEGRAAL method for collective assessment and decision-making in implementing regional plans. The report aims to identify the effective knowledge and tools to enable deliberations methodologies regarding practices on the sustainability of agriculture and biodiversity issues, societal responsibilities, and regional planning, concentrating on the question: “How to effectively mobilize resources (knowledge, tools, and methods) from different sources and at different scales regarding on agriculture and biodiversity issues to address sustainability challenges” that will create the scope for qualitative and quantitative assessments of sustainability as a new landmark of the agriculture sector.

Keywords: Biodiversity, Deliberation Support Tools, INTEGRAAL, stakeholder.

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

Abstract:

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

Abstract:

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: H. W. Corley

Abstract:

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: Qasim Idrees, Gao Liangtian, Liu Bo, Miao Yiran

Abstract:

In order to improve the efficiency and accuracy of the pressure hull structure, optimization of underwater vehicle based on response surface methodology, a method for optimizing the design of pressure hull structure was studied. To determine the pressure shell of five dimensions as a design variable, the application of thin shell theory and the Chinese Classification Society (CCS) specification was carried on the preliminary design. In order to optimize variables of the feasible region, different methods were studied and implemented such as Opt LHD method (to determine the design test sample points in the feasible domain space), parametric ABAQUS solution for each sample point response, and the two-order polynomial response for the surface model of the limit load of structures. Based on the ultimate load of the structure and the quality of the shell, the two-generation genetic algorithm was used to solve the response surface, and the Pareto optimal solution set was obtained. The final optimization result was 41.68% higher than that of the initial design, and the shell quality was reduced by about 27.26%. The parametric method can ensure the accuracy of the test and improve the efficiency of optimization.

Keywords: Parameterization, response surface, structure optimization, pressure hull.

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

Abstract:

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: Margareta Ilkova, Petr Teply

Abstract:

The article deals with dividends and their distribution from investors from a theoretical point of view. Some studies try to analyzed the reaction of the market on the dividend announcement and found out the change of dividend policy is associated with abnormal returns around the dividend announcement date. Another researches directly questioned the investors about their dividend preference and beliefs. Investors want the dividend from many reasons (e.g. some of them explain the dividend preference by the existence of transaction cost; investors prefer the dividend today, because there is less risky; the managers have private information about the firm). The most controversial theory of dividend policy was developed by Modigliani and Miller (1961) who demonstrated that in the perfect and complete capital markets the dividend policy is irrelevant and the value of the company is independent of its payout policy. Nevertheless, in the real world the capital markets are imperfect, because of asymmetric information, transaction costs, incomplete contracting possibilities and taxes.

Keywords: dividend distribution, taxation, payout policy, investor, Modigliani and Miller theorem

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

Abstract:

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: Galal H. Senussi, Muamar Benisa, Sanja Vasin

Abstract:

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: Prashant Kumar Tiwari, Yog Raj Sood

Abstract:

This paper proposes an investment cost recovery based efficient and fast sequential optimization approach to optimal allocation of thyristor controlled series compensator (TCSC) in competitive power market. The optimization technique has been used with an objective to maximizing the social welfare and minimizing the device installation cost by suitable location and rating of TCSC in the system. The effectiveness of proposed approach for location of TCSC has been compared with some existing methods of TCSC placement, in terms of its impact on social welfare, TCSC investment recovery and optimal generation as well as load patterns. The results have been obtained on modified IEEE 14-bus system.

Keywords: Double auction market, Investment cost recovery, Optimal location, Social welfare, TCSC

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Authors: Shyam S.N. Perera

Abstract:

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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