Search results for: optimization strategy

Authors: Deepa Das, Susmita Das

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Cognitive Radio (CR) is an emerging technology to combat the spectrum scarcity issues. This is achieved by consistently sensing the spectrum, and detecting the under-utilized frequency bands without causing undue interference to the primary user (PU). In soft decision fusion (SDF) based cooperative spectrum sensing, various evolutionary algorithms have been discussed, which optimize the weight coefficient vector for maximizing the detection performance. In this paper, we propose the hybrid invasive weed optimization and particle swarm optimization (IWO/PSO) algorithm as a fast and global optimization method, which improves the detection probability with a lesser sensing time. Then, the efficiency of this algorithm is compared with the standard invasive weed optimization (IWO), particle swarm optimization (PSO), genetic algorithm (GA) and other conventional SDF based methods on the basis of convergence and detection probability.

Keywords: cognitive radio, spectrum sensing, soft decision fusion, GA, PSO, IWO, hybrid IWO/PSO

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Authors: Nyumbaiza Tambwe

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The purpose of this paper is to demonstrate that hybrid urban agriculture as the most practiced type of urban agriculture in the majority of cities in sub-Saharan Africa can be taken as an alternative strategy in fighting food insecurity. The practice not only provides food, generates income and fights against unemployment; it constitutes a true back-up for households during crisis linked to the nature of capitalism system. African cities are mostly characterized by rapid population growth, rampant poverty, and high level of unemployment and food insecurity. Those factors and many others are at the origin of the emergence of urban agriculture in many African cities. Based particularly on results of research undertaken in the Democratic Republic of Congo (DRC), but also in comparison with those realized in other parts of the African continent, the paper is a case study. Therefore, the paper firstly describes the situation of food in Africa, secondly, presents hybrid urban agriculture as a household strategy in fighting food insecurity and finally shows possibilities and limits of this practice.

Keywords: alternative strategy, food security, household strategy, hybrid urban agriculture

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Authors: Hotlan Siagian, Hatane Semuel, Wilma Laura Sahetapy

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This study aims at examining the effect of market orientation on marketing performance through product adaptation strategy. The population of the research is domestic leather craft companies located in five regions, the center of the leather craft industry in Indonesia, i.e., Central Java, East Java, South Sulawesi, Bali, and West Kalimantan. The respondent consists of a manager level from each company. Data collection used a questionnaire designed with five-item Likert scale. Collected data were analyzed using structural equation modeling (SEM) technique with SmartPLS software version 3.0 to examine the hypotheses. The result of the study shows that all hypotheses are supported. Market orientation affects marketing performance. Market orientation affects product adaptation strategy. Product adaptation strategy influences the marketing performance. The research also has revealed the main finding that product adaptation strategy contributes to a mediating role in the market orientation strategy and marketing performance relationship. The leather craft companies in Indonesia, therefore, may refer to this result in improving their marketing performance.

Keywords: leather craft industry, market orientation, marketing performance, product adaptation strategy

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Authors: Chen Guo, Heng Tang, Ben Niu

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Clustering splits objects into different groups based on similarity, making the objects have higher similarity in the same group and lower similarity in different groups. Thus, clustering can be treated as an optimization problem to maximize the intra-cluster similarity or inter-cluster dissimilarity. In real-world applications, the datasets often have some complex characteristics: sparse, overlap, high dimensionality, etc. When facing these datasets, simultaneously optimizing two or more objectives can obtain better clustering results than optimizing one objective. However, except for the objectives weighting methods, traditional clustering approaches have difficulty in solving multi-objective data clustering problems. Due to this, evolutionary multi-objective optimization algorithms are investigated by researchers to optimize multiple clustering objectives. In this paper, the Data Clustering algorithm based on Multi-objective Periodic Bacterial Foraging Optimization with two Learning Archives (DC-MPBFOLA) is proposed. Specifically, first, to reduce the high computing complexity of the original BFO, periodic BFO is employed as the basic algorithmic framework. Then transfer the periodic BFO into a multi-objective type. Second, two learning strategies are proposed based on the two learning archives to guide the bacterial swarm to move in a better direction. On the one hand, the global best is selected from the global learning archive according to the convergence index and diversity index. On the other hand, the personal best is selected from the personal learning archive according to the sum of weighted objectives. According to the aforementioned learning strategies, a chemotaxis operation is designed. Third, an elite learning strategy is designed to provide fresh power to the objects in two learning archives. When the objects in these two archives do not change for two consecutive times, randomly initializing one dimension of objects can prevent the proposed algorithm from falling into local optima. Fourth, to validate the performance of the proposed algorithm, DC-MPBFOLA is compared with four state-of-art evolutionary multi-objective optimization algorithms and one classical clustering algorithm on evaluation indexes of datasets. To further verify the effectiveness and feasibility of designed strategies in DC-MPBFOLA, variants of DC-MPBFOLA are also proposed. Experimental results demonstrate that DC-MPBFOLA outperforms its competitors regarding all evaluation indexes and clustering partitions. These results also indicate that the designed strategies positively influence the performance improvement of the original BFO.

Keywords: data clustering, multi-objective optimization, bacterial foraging optimization, learning archives

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Authors: Tunjo Perić, Franjo Bratić

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In this paper the goal programming methodology for solving multiple objective problem of the technological variants and production plan optimization has been applied. The optimization criteria are determined and the multiple objective linear programming model for solving a problem of the technological variants and production plan optimization is formed and solved. Then the obtained results are analysed. The obtained results point out to the possibility of efficient application of the goal programming methodology in solving the problem of the technological variants and production plan optimization. The paper points out on the advantages of the application of the goal programming methodolohy compare to the Surrogat Worth Trade-off method in solving this problem.

Keywords: goal programming, multi objective programming, production plan, SWT method, technological variants

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Authors: Helen S. Ghali, Haidy S. Ghali, Salma Ibrahim, Ossama Hosny, Hatem S. Elbehairy

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Infrastructure systems are essential assets in any community; accordingly, authorities aim to maximize its life span while minimizing the life cycle cost. This requires studying the asset conditions throughout its operation and forming a cost-efficient maintenance strategy plan. The objective of this study is to develop a highway management system that provides medium-term maintenance plans with the minimum life cycle cost subject to budget constraints. The model is applied to data collected for the highway network in India with the aim to output a 5-year maintenance plan strategy from 2019 till 2023. The main element considered is the surface coarse, either rigid or flexible pavement. The model outputs a 5-year maintenance plan for each segment given the budget constraint while maximizing the new pavement condition rating and minimizing its life cycle cost.

Keywords: infrastructure, asset management, optimization, maintenance plan

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Authors: Khodamorad Nabaki, Jianhu Shen, Xiaodong Huang

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This paper develops a method for considering the critical fatigue stress as a constraint in the Bi-directional Evolutionary Structural Optimization (BESO) method. Our aim is to reach an optimal design in which high cycle fatigue failure does not occur for a specific life time. The critical fatigue stress is calculated based on modified Goodman criteria and used as a stress constraint in our topology optimization problem. Since fatigue generally does not occur for compressive stresses, we use the p-norm approach of the stress measurement that considers the highest tensile principal stress in each point as stress measure to calculate the sensitivity numbers. The BESO method has been extended to minimize volume an object subjected to the critical fatigue stress constraint. The optimization results are compared with the results from the compliance minimization problem which shows clearly the merits of our newly developed approach.

Keywords: topology optimization, BESO method, p-norm, fatigue constraint

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Authors: Inayat Ur Rehman, Georgia Sakellari

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Cloud computing has evolved into a vital technology for businesses, offering scalability, flexibility, and cost-effectiveness. However, maintaining high availability and optimal performance in the cloud is crucial for reliable services. This paper explores the significance of cloud monitoring and performance optimization in sustaining the high availability of cloud-based systems. It discusses diverse monitoring tools, techniques, and best practices for continually assessing the health and performance of cloud resources. The paper also delves into performance optimization strategies, including resource allocation, load balancing, and auto-scaling, to ensure efficient resource utilization and responsiveness. Addressing potential challenges in cloud monitoring and optimization, the paper offers insights into data security and privacy considerations. Through this thorough analysis, the paper aims to underscore the importance of cloud monitoring and performance optimization for ensuring a seamless and highly available cloud computing environment.

Keywords: cloud computing, cloud monitoring, performance optimization, high availability, scalability, resource allocation, load balancing, auto-scaling, data security, data privacy

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Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper presents a Guidance and Control (G&C) strategy to address spacecraft maneuvering problem for future Rendezvous and Docking (RVD) missions. The proposed strategy allows safe and propellant efficient trajectories for space servicing missions including tasks such as approaching, inspecting and capturing. This work provides the validation test results of the G&C laws using a Hardware-In-the-Loop (HIL) setup with two robotic mockups representing the chaser and the target spacecraft. Through this paper, the challenges of the relative motion control in space are first summarized, and in particular, the constraints imposed by the mission, spacecraft and, onboard processing capabilities. Second, the proposed algorithm is introduced by presenting the formulation of constrained Model Predictive Control (MPC) to optimize the fuel consumption and explicitly handle the physical and geometric constraints in the system, e.g. thruster or Line-Of-Sight (LOS) constraints. Additionally, the coupling between translational motion and rotational motion is addressed via dual quaternion based kinematic description and accordingly explained. The resulting convex optimization problem allows real-time implementation capability based on a detailed discussion on the computational time requirements and the obtained results with respect to the onboard computer and future trends of space processors capabilities. Finally, the performance of the algorithm is presented in the scope of a potential future mission and of the available equipment. The results also cover a comparison between the proposed algorithms with Linear–quadratic regulator (LQR) based control law to highlight the clear advantages of the MPC formulation.

Keywords: autonomous vehicles, embedded optimization, real-time experiment, rendezvous and docking, space robotics

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Authors: Ayudhia P. Gusti, Semin

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It is known that total operating cost of a vessel is dominated by the cost of fuel consumption. How to reduce the fuel cost of ship so that the operational costs of fuel can be minimized is the question that arises. As the basis of these kinds of problem, sailing speed determination is an important factor to be considered by a shipping company. Optimal speed determination will give a significant influence on the route and berth schedule of ships, which also affect vessel operating costs. The purpose of this paper is to clarify some important issues about ship speed optimization. Sailing speed, displacement, sailing time, and specific fuel consumption were obtained from shipping log data to be further analyzed for modeling the speed optimization. The presented speed optimization model is expected to affect the fuel consumption and to reduce the cost of fuel consumption.

Keywords: maritime transportation, reducing fuel, shipping log data, speed optimization

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Authors: Taisir Eldos, Aws Kanan, Waleed Nazih, Ahmad Khatatbih

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Chemical Reaction Optimization (CRO) is an optimization metaheuristic inspired by the nature of chemical reactions as a natural process of transforming the substances from unstable to stable states. Starting with some unstable molecules with excessive energy, a sequence of interactions takes the set to a state of minimum energy. Researchers reported successful application of the algorithm in solving some engineering problems, like the quadratic assignment problem, with superior performance when compared with other optimization algorithms. We adapted this optimization algorithm to the Printed Circuit Board Drilling Problem (PCBDP) towards reducing the drilling time and hence improving the PCB manufacturing throughput. Although the PCBDP can be viewed as instance of the popular Traveling Salesman Problem (TSP), it has some characteristics that would require special attention to the transactions that explore the solution landscape. Experimental test results using the standard CROToolBox are not promising for practically sized problems, while it could find optimal solutions for artificial problems and small benchmarks as a proof of concept.

Keywords: evolutionary algorithms, chemical reaction optimization, traveling salesman, board drilling

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Authors: Ali Motalebi Saraji, Reza Zarei Lamuki

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Speed control and behavior improvement of permanent magnet synchronous motors (PMSM) that have reliable performance, low loss, and high power density, especially in industrial drives, are of great importance for researchers. Because of its importance in this paper, coefficients optimization of proportional-integrator-derivative fractional order controller is presented using Particle Swarm Optimization (PSO) algorithm in order to improve the behavior of PMSM in its speed control loop. This improvement is simulated in MATLAB software for the proposed optimized proportional-integrator-derivative fractional order controller with a Genetic algorithm and compared with a full order controller with a classic optimization method. Simulation results show the performance improvement of the proposed controller with respect to two other controllers in terms of rising time, overshoot, and settling time.

Keywords: speed control loop of permanent magnet synchronous motor, fractional and full order proportional-integrator-derivative controller, coefficients optimization, particle swarm optimization, improvement of behavior

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Authors: Mohammad Mehdi Mazarei, Ali Asghar Behroozpoor

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In this paper, we define an optimization problem corresponding to smooth and nonsmooth functions which its optimal solution is the first derivative of these functions in a domain. For this purpose, a linear programming problem corresponding to optimization problem is obtained. The optimal solution of this linear programming problem is the approximate generalized first derivative. In fact, we approximate generalized first derivative of nonsmooth functions as tailor series. We show the efficiency of our approach by some smooth and nonsmooth functions in some examples.

Keywords: general derivative, linear programming, optimization problem, smooth and nonsmooth functions

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Authors: Michal Kopcek, Tomas Skulavik, Michal Kebisek, Gabriela Krizanova

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The operation of nuclear power plants involves continuous monitoring of the environment in their area. This monitoring is performed using a complex data acquisition system, which collects status information about the system itself and values of many important physical variables e.g. temperature, humidity, dose rate etc. This paper describes a proposal and optimization of communication that takes place in teledosimetric system between the central control server responsible for the data processing and storing and the decentralized measuring stations, which are measuring the physical variables. Analyzes of ongoing communication were performed and consequently the optimization of the system architecture and communication was done.

Keywords: communication protocol, transmission optimization, data acquisition, system architecture

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Authors: Fatin Khairani Khairul 'Azam

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Reading comprehension requires the formation of an articulate mental representation of the information in a text. It involves three interdepended elements—the reader, the text, and the activity, all situated into an extensive sociocultural context. Incorporating metacognitive think-aloud strategy into teaching reading comprehension would improve learners’ reading comprehension skills as it helps to monitor their thinking as they read. Furthermore, by integrating Digital Educational Learning Initiative Malaysia (DELIMa) platform in teaching reading comprehension, it can make the process interactive and fun. A quasi-experimental one-group pre-test post-test design was used to identify the effectiveness of using metacognitive think-aloud strategy via DELIMa platform in improving pupils’ reading comprehension performance and their perceptions towards reading comprehension. The participants of the study comprised 82 of form 1 pupils from a secondary school in Pasir Gudang, Johor, Malaysia. All participants were required to sit for pre-and post-tests to track their reading comprehension performance and perceptions. The findings revealed that incorporating metacognitive think-aloud strategy is an effective strategy in teaching reading comprehension as the performance of pupils in reading comprehension and their perceptions towards reading comprehension were improved during the post tests. It is hoped that the findings of the study would be useful to the teachers incorporating the same strategy in teaching to improve pupils' reading skills. It is suggested that future study should involve the motivation factor of the participants on incorporating think-aloud strategy into teaching reading comprehension as well.

Keywords: DELIMa Platform, ESL Learners, Metacognitive Strategy, Pupils' Perceptions, Reading Comprehension, Think-Aloud Strategy

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Authors: Maria Hornell, Marcus Ohman

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Nature, and the society it is a part of, is under constant change. The landscape, climate and game populations vary over time, as well as society's priorities and the way it uses the land where wildlife may proliferate. Sweden currently has historically large wildlife populations which are a resource for the benefit and joy of many people. Wildlife may also be seen as a problem as it may cause damage in contradiction to other human interests. The Swedish Environmental Protection Agency introduces a new long-term strategy for national wildlife management. The strategy envisions a wildlife management in balance. It focuses on wildlife values in a broad sense including outdoor recreation and tourism as well as conservation of biodiversity. It is fundamental that these values should be open and accessible for the major part of the population. For that to be possible new ways to manage, mitigate and prevent damages and other problems that wildlife causes need to be developed. The strategy describes a roadmap for the development and strengthening of Sweden's wildlife management until 2020. It aims at being applicable for those authorities and stakeholders with interest in wildlife management being a guide for their own strategies, goals, and activities.

Keywords: wildlife management, strategy, Sweden, SEPA

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Authors: Filippo Ranalli, Forest Flager, Martin Fischer

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This paper presents a ground structure method to optimize the topology and discrete member sizing of steel frame structures in order to minimize total installed cost, including material, fabrication and erection components. The proposed method improves upon existing cost-based ground structure methods by incorporating constructability considerations well as satisfying both strength and serviceability constraints. The architecture for the method is a bi-level Multidisciplinary Feasible (MDF) architecture in which the discrete member sizing optimization is nested within the topology optimization process. For each structural topology generated, the sizing optimization process seek to find a set of discrete member sizes that result in the lowest total installed cost while satisfying strength (member utilization) and serviceability (node deflection and story drift) criteria. To accurately assess cost, the connection details for the structure are generated automatically using accurate site-specific cost information obtained directly from fabricators and erectors. Member continuity rules are also applied to each node in the structure to improve constructability. The proposed optimization method is benchmarked against conventional weight-based ground structure optimization methods resulting in an average cost savings of up to 30% with comparable computational efficiency.

Keywords: cost-based structural optimization, cost-based topology and sizing, optimization, steel frame ground structure optimization, multidisciplinary optimization of steel structures

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Authors: Kanyapat U. Tapao

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The purpose of this study is to analyze the operation strategy strategies and public relations trend for public relations strategies development in public television station in Thailand. This study is a qualitative approach by indent interview from the 6 key informants that are managers of Voice TV and Thairath TV Channel. The results showed that both TV stations have to do research before making a release on the operation strategy policy such as a slogan, segmentation, integrated marketing communication and PR activity and also in term of Public Relations trend are including online media, online content and online training before opening the station and start promoting. By the way, we found the PR strategy for both TV station should be including application on mobile, online content, CRM activity, online banner, special event, and brand ambassador in order to bring a very reliable way.

Keywords: online banner, operation strategy, public relations trend, public relations strategies development

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Authors: Imam Uddin, Imtiaz Ahmed Memon

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This paper analyzes the ideological contextuality of market oriented strategy language used by Industry leaders to envision the future of Islamic financial Institutions (IFIs) in the light of Wittgenstein language-games and Foucault’s power-discourse framework. The analysis infers that the explicit market orientation of strategy language and modern knowledge of finance now defines various concepts related of Islamic finance, let alone Islamic finance theory itself. Theorizing and practicing Islamic finance therefore under the dominant influence of modern strategy discourse and modern knowledge of finance has significant implications for developing an ethical and spiritual orientation of Islamic banks. The concerned academia and scholarship therefore need to review such trends and work around the possible degradation to the public image of IFIs and resulting disappointments of religiously inspired customers.

Keywords: Islamic finance discourse, strategy discourse, language games, strategic intent, productive misunderstanding

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Authors: Young Sik Kim, Tae Kwon Ha

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This article considers the problems of economic growth and Russian energy strategy. Also in this paper, the issues related to the economic growth prospects of Russian were discussed. Russian energy strategy without standing Russia`s stature in global energy markets, at the current production and extraction rates, will not be able to sustain its own production as well as fulfil its energy strategy. Indeed, Russia’s energy sector suffers from a chronic lack of investments which are necessary to modernize its energy supply system. In recent years, especially since the international financial crisis, Russia-EU energy cooperation has made substantive progress. Recently the break-through progress has been made, resulting mainly from long-term contributing factors between the countries and recent international economic and political situation changes. Analytical material presented in the article is intended for a more detailed or substantive analysis related to foreign economic relations of the countries and Russia as well.

Keywords: Russia, energy strategy, economic growth, cooperation

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Authors: Suneel Kumar, Nanda Kumar J. Sreelal Sreedhar, Suchibrata Sen, V. Muralidharan,

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Fan technology is very critical and crucial for any aero engine technology. The fan disc forms a critical part of the fan module. It is an airworthiness requirement to have a metrological qualified quality disc. The current study uses a tactile probing and scanning on an articulated measuring machine (AMM), a bridge type coordinate measuring machine (CMM) and Metrology software for intermediate and final dimensional and geometrical verification during the prototype development of the disc manufactured through forging and machining process. The circumferential dovetails manufactured through the milling process are evaluated based on the evaluated and analysed metrological process. To perform metrological optimization a change of philosophy is needed making quality measurements available as fast as possible to improve process knowledge and accelerate the process but with accuracy, precise and traceable measurements. The offline CMM programming for inspection and optimisation of the CMM inspection plan are crucial portions of the study and discussed. The dimensional measurement plan as per the ASME B 89.7.2 standard to reach an optimised CMM measurement plan and strategy are an important requirement. The probing strategy, stylus configuration, and approximation strategy effects on the measurements of circumferential dovetail measurements of the developmental prototype disc are discussed. The results were discussed in the form of enhancement of the R &R (repeatability and reproducibility) values with uncertainty levels within the desired limits. The findings from the measurement strategy adopted for disc dovetail evaluation and inspection time optimisation are discussed with the help of various analyses and graphical outputs obtained from the verification process.

Keywords: coordinate measuring machine, CMM, aero engine, articulated measuring machine, fan disc

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Authors: Zunaira Asif, Zhi Chen

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The sustainable measures on air quality management are recognized as one of the most serious environmental concerns in the mining region. The mining operations emit various types of pollutants which have significant impacts on the environment. This study presents a stochastic control strategy by developing the air pollution control model to achieve a cost-effective solution. The optimization method is formulated to predict the cost of treatment using linear programming with an objective function and multi-constraints. The constraints mainly focus on two factors which are: production of metal should not exceed the available resources, and air quality should meet the standard criteria of the pollutant. The applicability of this model is explored through a case study of an open pit metal mine, Utah, USA. This method simultaneously uses meteorological data as a dispersion transfer function to support the practical local conditions. The probabilistic analysis and the uncertainties in the meteorological conditions are accomplished by Monte Carlo simulation. Reasonable results have been obtained to select the optimized treatment technology for PM_2.5, PM₁₀, NO_x, and SO₂. Additional comparison analysis shows that baghouse is the least cost option as compared to electrostatic precipitator and wet scrubbers for particulate matter, whereas non-selective catalytical reduction and dry-flue gas desulfurization are suitable for NO_x and SO₂ reduction respectively. Thus, this model can aid planners to reduce these pollutants at a marginal cost by suggesting control pollution devices, while accounting for dynamic meteorological conditions and mining activities.

Keywords: air pollution, linear programming, mining, optimization, treatment technologies

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Authors: Khan Shahid, Shahid Zakia

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This article explores the fields of Theology and Islamic Philosophy in alignment with the SOUL (Sincere act, Optimization efforts, Ultimate goal, Law compliance) framework. It examines their historical development and demonstrates how embracing sincerity, optimization, ultimate goals, and law compliance enhances these disciplines within the Islamic context. By emphasizing the importance of Sincere acts, Optimization efforts, Ultimate goal, and Law compliance, this article provides a framework for enriching Theology and Islamic Philosophy.

Keywords: SOUL framework, Theology, Islamic Philosophy, Sincerity act, Optimization effort, Ultimate goal, Law compliance

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Authors: Mohammed Belloufi, Rachid Benzine, Badreddine Sellami

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Conjugate gradient methods is useful for solving large scale optimization problems in scientific and engineering computation, characterized by the simplicity of their iteration and their low memory requirements. It is well known that the search direction plays a main role in the line search method. In this paper, we propose a search direction with the Wolfe line search technique for solving unconstrained optimization problems. Under the above line searches and some assumptions, the global convergence properties of the given methods are discussed. Numerical results and comparisons with other CG methods are given.

Keywords: unconstrained optimization, conjugate gradient method, strong Wolfe line search, global convergence

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Authors: Akshay Paranjape, Nils Plettenberg, Robert Schmitt

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Producing faulty products can be costly for manufacturing companies and wastes resources. To reduce scrap rates in manufacturing, process parameters can be optimized using machine learning. Thus far, research mainly focused on optimizing specific processes using traditional algorithms. To develop a framework that enables real-time optimization based on a predictive model for an arbitrary production process, this study explores the application of reinforcement learning (RL) in this field. Based on a thorough review of literature about RL and process parameter optimization, a model based on maximum a posteriori policy optimization that can handle both numerical and categorical parameters is proposed. A case study compares the model to state–of–the–art traditional algorithms and shows that RL can find optima of similar quality while requiring significantly less time. These results are confirmed in a large-scale validation study on data sets from both production and other fields. Finally, multiple ways to improve the model are discussed.

Keywords: reinforcement learning, production process optimization, evolutionary algorithms, policy optimization, actor critic approach

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Authors: Thiago Ribeiro de Alencar, Jacyro Gramulia Junior, Patricia Teixeira Leite

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The area of the electricity sector that deals with energy needs by the hydroelectric in a coordinated manner is called Operation Planning of Hydrothermal Power Systems (OPHPS). The purpose of this is to find a political operative to provide electrical power to the system in a given period, with reliability and minimal cost. Therefore, it is necessary to determine an optimal schedule of generation for each hydroelectric, each range, so that the system meets the demand reliably, avoiding rationing in years of severe drought, and that minimizes the expected cost of operation during the planning, defining an appropriate strategy for thermal complementation. Several optimization algorithms specifically applied to this problem have been developed and are used. Although providing solutions to various problems encountered, these algorithms have some weaknesses, difficulties in convergence, simplification of the original formulation of the problem, or owing to the complexity of the objective function. An alternative to these challenges is the development of techniques for simulation optimization and more sophisticated and reliable, it can assist the planning of the operation. Thus, this paper presents the development of a computational tool, namely Hydro-IA for solving optimization problem identified and to provide the User an easy handling. Adopted as intelligent optimization technique is Genetic Algorithm (GA) and programming language is Java. First made the modeling of the chromosomes, then implemented the function assessment of the problem and the operators involved, and finally the drafting of the graphical interfaces for access to the User. The results with the Genetic Algorithms were compared with the optimization technique nonlinear programming (NLP). Tests were conducted with seven hydroelectric plants interconnected hydraulically with historical stream flow from 1953 to 1955. The results of comparison between the GA and NLP techniques shows that the cost of operating the GA becomes increasingly smaller than the NLP when the number of hydroelectric plants interconnected increases. The program has managed to relate a coherent performance in problem resolution without the need for simplification of the calculations together with the ease of manipulating the parameters of simulation and visualization of output results.

Keywords: energy, optimization, hydrothermal power systems, artificial intelligence and genetic algorithms

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Authors: Rohit Mittal, Bright Keswani, Amit Mithal

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This paper provides a sense about the application of computational intelligence techniques used to develop computer games, especially car racing. For the deep sense and knowledge of artificial intelligence, this paper is divided into various sections that is optimization, imitation, innovation and combining approach of optimization and imitation. This paper is mainly concerned with combining approach which tells different aspects of using fitness measures and supervised learning techniques used to imitate aspects of behavior. The main achievement of this paper is based on modelling player behaviour and evolving new game content such as racing tracks as single car racing on single track.

Keywords: evolution algorithm, genetic, optimization, imitation, racing, innovation, gaming

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Authors: Amit Saraswat, Ruchi Tewari

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Purpose: The research paper aims at understanding the alignment of business and IT in the Indian context and the business value attached to such an alignment. Methodology: The study is conducted in two stages. Stage one: Bibliographic research was conducted to evolve the parameters for defining alignment. Stage two: Evolving a model for strategic alignment to conduct an empirical study. The model is defined in terms of four fundamental domains of strategic management choice – business strategy, information strategy, organizational structure, and information technology structure. A survey through a questionnaire was conducted across organizations from 4 different industries and Structure Equation Modelling (SEM) technique is used for validating the model. Findings: In the Indian scenario all the subscales of alignment could not be validated. It could be validated that organizational strategy impacts information strategy and information technology structure. Research Limitations: The study is limited to the Indian context. Business IT alignment may be culture dependent so further research is required to validate the model in other cultures. Originality/Value: In the western world several models of alignment of business strategy and information systems is available but they do not measure the extent of alignment which the current study in the Indian context. Findings of the study can be used by managers in strategizing and understanding their business and information systems needs holistically and cohesively leading to efficient use of resources and output.

Keywords: business strategy, information technology (IT), business IT alignment, SEM

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Authors: Magdi M. Nabi, Ding-Li Yu

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This paper presents a neural network based model predictive control (MPC) strategy to control a strongly exothermic reaction with complicated nonlinear kinetics given by Chylla-Haase polymerization reactor that requires a very precise temperature control to maintain product uniformity. In the benchmark scenario, the operation of the reactor must be guaranteed under various disturbing influences, e.g., changing ambient temperatures or impurity of the monomer. Such a process usually controlled by conventional cascade control, it provides a robust operation, but often lacks accuracy concerning the required strict temperature tolerances. The predictive control strategy based on the RBF neural model is applied to solve this problem to achieve set-point tracking of the reactor temperature against disturbances. The result shows that the RBF based model predictive control gives reliable result in the presence of some disturbances and keeps the reactor temperature within a tight tolerance range around the desired reaction temperature.

Keywords: Chylla-Haase reactor, RBF neural network modelling, model predictive control, semi-batch reactors

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Authors: Min Zhou, Kaixuan Lin, Yaping Huang

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In this paper, the industrial space of metropolitan area in Wuhan is taken as a sample. First of all, it puts forward that the structure of service economy, circle gradient relocation and high degree of regional collaboration are the rules of industrial spatial development in the modern world cities. Secondly, using the economic statistics and land use vector data (1993, 2004, 2010, and 2013) of Wuhan, it analyzes the present situation of industry development and the characteristics of industrial space layout from three aspects of the industrial economic structure, industrial layout, and industrial regional synergy. Then, based on the industrial development regularity of world cities, it puts forward to construct the industrial spatial level of ‘complex industrial concentration area + modular industry unit’ and the industrial spatial structure of ‘13525’. Finally, it comes up with the optimization tactics of the industrial space’s transformation in the future under the background of new economic era.

Keywords: big city of metropolitan area, industrial space, characteristics, layout, strategy

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