Search results for: foundation optimization

Authors: A. Ramalho, L. Romeiro, R. Ventura, A. Suleman

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A real-time path planning framework for Unmanned Air Vehicles, and in particular multi-rotors is proposed. The framework is designed to provide feasible trajectories from the current UAV position to a goal state, taking into account constraints such as obstacle avoidance, problem kinematics, and vehicle limitations such as maximum speed and maximum acceleration. The framework computes feasible paths online, allowing to avoid new, unknown, dynamic obstacles without fully re-computing the trajectory. These features are achieved using an iterative process in which the robot computes and optimizes the trajectory while performing the mission objectives. A first trajectory is computed using a modified Rapidly-Exploring Random Tree (RRT) algorithm, that provides trajectories that respect a maximum curvature constraint. The trajectory optimization is accomplished using the Interior Point Optimizer (IPOPT) as a solver. The framework has proven to be able to compute a trajectory and optimize to a locally optimal with computational efficiency making it feasible for real-time operations.

Keywords: interior point optimization, multi-rotors, online path planning, rapidly exploring random trees, trajectory optimization

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Authors: Edward Ridyard, Vinary Varadarajan

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Background and Aims: The first year as a doctor in any country represents a major career transition in any physician's life. During this period, many physicians concentrate on obtaining clinical skills but may not obtain the important skills necessary to cope with stress. In this study we elucidate stress levels amongst FY1 doctors regarding the transitioning into specialty career choices, working in the NHS and anxiety about future career success. Methods: A prospective single blinded analysis of Foundation Year one (FY1) trainees using a non-mandatory online questionnaire was distributed. No exclusion criteria were applied. The only inclusion criteria was the doctor was in a full-time FY1 post and this was their first job in the UK. A total of n= 22 doctors were included in the study. After data collection, statistical analysis using chi-squared testing was applied. Results: The large majority of FY1 doctors (72.7%) already knew what specialty they wished to pursue (p=0.0001). With regards to their future careers 45.5% of FY1 doctors stated "above average" stress levels. The majority of FY1 doctors (64.3%) stated their stress levels working in the NHS were either "above average" or "high". Finally, 81.8% of respondents know colleagues who have been put off from pursuing specialties due to the stress of competition. Conclusions: A large majority of FY1 doctors already know at this early stage what area they would like to specialise in. With this in mind, a large proportion have above "average" levels of stress with regards to securing this future career path. The most worrying finding is that 64.3% of FY1s stated they had "above average" or "high" stress levels working in the NHS. We therefore recommend formal stress management education to be incorporated into the foundation programme curriculum.

Keywords: stress, anxiety, junior doctor, education

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Authors: Darwin Castillo Huamaní, Francisco A. M. Gomes

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The aim of the multi-material topology optimization (MTO) is to obtain the optimal topology of structures composed by many materials, according to a given set of constraints and cost criteria. In this work, we seek the optimal distribution of materials in a domain, such that the flexibility of the structure is minimized, under certain boundary conditions and the intervention of external forces. In the case we have only one material, each point of the discretized domain is represented by two values from a function, where the value of the function is 1 if the element belongs to the structure or 0 if the element is empty. A common way to avoid the high computational cost of solving integer variable optimization problems is to adopt the Solid Isotropic Material with Penalization (SIMP) method. This method relies on the continuous interpolation function, power function, where the base variable represents a pseudo density at each point of domain. For proper exponent values, the SIMP method reduces intermediate densities, since values other than 0 or 1 usually does not have a physical meaning for the problem. Several extension of the SIMP method were proposed for the multi-material case. The one that we explore here is the ordered SIMP method, that has the advantage of not being based on the addition of variables to represent material selection, so the computational cost is independent of the number of materials considered. Although the number of variables is not increased by this algorithm, the optimization subproblems that are generated at each iteration cannot be solved by methods that rely on second derivatives, due to the cost of calculating the second derivatives. To overcome this, we apply a globally convergent version of the sequential linear programming method, which solves a linear approximation sequence of optimization problems.

Keywords: globally convergence, multi-material design ordered simp, sequential linear programming, topology optimization

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Authors: Karima Megdouli, Bourhan tachtouch

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Ejector refrigeration cycles offer an alternative to conventional systems for producing cold from low-temperature heat. In this article, a thermodynamic model is presented. This model has the advantage of simplifying the calculation algorithm and describes the complex double-throttling mechanism that occurs in the ejector. The model assumption and calculation algorithm are presented first. The impact of each efficiency is evaluated. Validation is performed on several data sets. The ejector model is then used to simulate a RES (refrigeration ejector system), to validate its robustness and suitability for use in predicting thermodynamic cycle performance. A Taguchi and ANOVA optimization is carried out on a RES. TOPSIS analysis was applied to decide the optimum refrigerants with cost, safety, environmental and enviro economic concerns along with thermophysical properties.

Keywords: ejector, velocity distribution, shock circle, Taguchi and ANOVA optimization, TOPSIS analysis

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Authors: Zahra Mohagheghian, Fatema Agharebparast

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The comparative study of religions is one of the ways which provides peace and makes the believers of religions closer together. Finding the common notions could be a foundation for the dialog among the monotheistic religions and a background to eliminate the misunderstandings and to reach common point of views. The cornerstone of all the common efforts of the believers of the religions is to reach an understanding for building a better world where true peace is established. So, the article seeks to verify the notion of positive thinking in the religious resources of Islam and Christianity. In order to understand the foundations of the religious teachings and to provide a better understanding among the believers, then, the article tries to discover the common fundamentals and the opposing points about the positive thinking in these two religions. We first try to explain the notion of positive thinking in Islam and Christianity and then offer recommended ways in both religions to create and to strengthen this way of thinking. As the different parts of the New Testament is not theologically homogeneous, this collection has been verified and explained in four different parts: Three Gospels (Matthew, Mark and Luke), John's thoughts, thoughts and ideas of Paul and finally the Christian sects . The findings of the survey show that the notion of positive thinking in the monotheistic religions of Islam and Christianity can be traced back by the keyword "hope". It is only the hope which could finally create the soul of positive attitude and thinking inside the humankind. This hope is accompanied by the prospect and causes the humankind to work hard to reach their goals. However, there are some opposing points in these two religions about the basic foundation of this true hope. From the Quran viewpoint, the main foundation of the hope is God and the human is obliged to follow his worldly goals in accordance with this foundation as well as faith to God and avoidance of committing sins. On the other hand, the basic foundation of hope in the Three Gospels (Matthew, Mark and Luke) and the teachings of Paul is the promise of a coming Kingdom. Although there are some opposing views about the meaning of this as well as the ways to attain this hope, this hope is generally related to the purpose of human life and afterlife. The Christ, in the John's thoughts, is the source of hope and everybody, believing in God, must also have hope for Jesus Christ. Effects and functions of such hope are strengthening the spirit of love and kindness to others. Hence, in Christianity, the hope and positive thinking about the future, along with good deeds, reflects different viewpoints. On the other hand, in Quran, this is faith to God and fulfilling the Sharia orders which ignite and strengthen this hope and way of thinking. This is the base that continues nowadays with Vilāya and the love for Ahlulbeit in the Shiite views.

Keywords: God, new testament, positive thinking, Quran

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Authors: Mostafa M. Abo Elsoud, Heba I. Elkhouly, Nagwa M. Sidkey

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Production of rhamnolipids by Pseudomonas aeruginosa has attracted a growing interest during the last few decades due to its high productivity compared with other microorganisms. In the current work, rhamnolipids production by P. aeruginosa PAO1 was statistically modeled using Taguchi orthogonal array, numerically optimized and validated. Prickly Pear Peel (Opuntia ficus-indica) has been used as a carbon source for production of rhamnolipid. Finally, the optimum conditions for rhamnolipid production were applied in 5L working volume bioreactors at different aerations, agitation and controlled pH for maximum rhamnolipid production. In addition, kinetic studies of rhamnolipids production have been reported. At the end of the batch bioreactor optimization process, rhamnolipids production by P. aeruginosa PAO1 has reached the worldwide levels and can be applied for its industrial production.

Keywords: rhamnolipids, pseudomonas aeruginosa, statistical optimization, tagushi, opuntia ficus-indica

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Authors: Tsegay Giday Woldu, Haibin Zhang, Xin Zhang, Yemane Hailu Fissuh

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It is well known that nonlinear conjugate gradient method is one of the widely used first order methods to solve large scale unconstrained smooth optimization problems. Because of the low memory requirement, attractive theoretical features, practical computational efficiency and nice convergence properties, nonlinear conjugate gradient methods have a special role for solving large scale unconstrained optimization problems. Large scale optimization problems are with important applications in practical and scientific world. However, nonlinear conjugate gradient methods have restricted information about the curvature of the objective function and they are likely less efficient and robust compared to some second order algorithms. To overcome these drawbacks, the new modified nonlinear conjugate gradient method is presented. The noticeable features of our work are that the new search direction possesses the sufficient descent property independent of any line search and it belongs to a trust region. Under mild assumptions and standard Wolfe line search technique, the global convergence property of the proposed algorithm is established. Furthermore, to test the practical computational performance of our new algorithm, numerical experiments are provided and implemented on the set of some large dimensional unconstrained problems. The numerical results show that the proposed algorithm is an efficient and robust compared with other similar algorithms.

Keywords: conjugate gradient method, global convergence, large scale optimization, sufficient descent property

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Authors: Elijah Cavan

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In Major League Sports (MLB, NBA, NHL, NFL), it is the Front Office Staff (FOS) who make decisions about who plays for their respective team. The FOS bear the brunt of the responsibility for acquiring players through drafting, trading and signing players in free agency while typically contesting with maximum roster salary constraints. The players themselves are volatile assets of these teams- their value fluctuates with age and performance. A simple comparison can be made when viewing players as assets. The problem here is similar to that of optimizing your investment portfolio. The The goal is ultimately to maximize your periodic returns while tolerating a fixed risk (degree of uncertainty/ potential loss). Each franchise may value assets differently, and some may only tolerate lower risk levels- these are examples of factors that introduce additional constraints into the model. In this talk, we will detail the mathematical formulation of this problem as a constrained optimization problem- which can be solved with classical machine learning methods but is also well posed as a problem to be solved on quantum computers

Keywords: optimization, financial mathematics, sports analytics, simulated annealing

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Authors: K. K. Saijaand, K. Prabhakaran Nair

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This study aims to determine change in optimal lo-cations of dual trailing-edge flaps for various thrust coefficient to solidity (Ct /σ) ratios of helicopter to achieve minimum hub vibration levels, with low penalty in terms of required trailing-edge flap control power. Polynomial response functions are used to approximate hub vibration and flap power objective functions. Single objective and multi-objective optimization is carried with the objective of minimizing hub vibration and flap power. The optimization results shows that the inboard flap location at low Ct/σ ratio move farther from the baseline value and at high Ct/σ ratio move towards the root of the blade for minimizing hub vibration.

Keywords: helicopter rotor, trailing-edge flap, thrust coefficient to solidity (Ct /σ) ratio, optimization

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Authors: Mohammad Ibrahim

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The study was conducted at Albasar international foundation ophthalmic hospitals in Sudan to study the burden and patterns of ophthalmic disorder in the sector. Review of the hospitals records revealed that the total number of patient examined in the hospitals and outreached camps conducted by the hospitals is 10,513,874, the total number of surgeries is 694,015 and the total number of pupils at school program is 230,382. The organization working with the highest management system and standards and quality result based planning. The study yielded that the ophthalmic problem in Sudan are of great percentage and the temporal blindness disorder are high since major cases and surgeries were Cataract (57.8%). Retinal problem (2.9%), Glaucoma (2.4%), Orbit and Occulo-plastic disorders (2.2%) other disorders are refractive errors, squint and strabismus, Corneal, Pediatrics and minor ophthalmic disorders.

Keywords: hospitals and outreach ophthalmic services, largest coverage of ophthalmic services, nonprofitable ophthalmic services, strong management system and standards

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Authors: Dibakar Chakrabarty, Mebada Suiting

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Rapid urbanization coupled with changes in land use pattern results in increasing peak discharge and shortening of catchment time of concentration. The consequence is floods, which often inundate roads and inhabited areas of cities and towns. Management of storm water resulting from rainfall has, therefore, become an important issue for the municipal bodies. Proper management of storm water obviously includes adequate design of storm water drainage networks. The design of storm water network is a costly exercise. Least cost design of storm water networks assumes significance, particularly when the fund available is limited. Optimal design of a storm water system is a difficult task as it involves the design of various components, like, open or closed conduits, storage units, pumps etc. In this paper, a methodology for least cost design of storm water drainage systems is proposed. The methodology proposed in this study consists of coupling a storm water simulator with an optimization method. The simulator used in this study is EPA’s storm water management model (SWMM), which is linked with Genetic Algorithm (GA) optimization method. The model proposed here is a mixed integer nonlinear optimization formulation, which takes care of minimizing the sectional areas of the open conduits of storm water networks, while satisfactorily conveying the runoff resulting from rainfall to the network outlet. Performance evaluations of the developed model show that the proposed method can be used for cost effective design of open conduit based storm water networks.

Keywords: genetic algorithm (GA), optimal design, simulation-optimization, storm water network, SWMM

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Authors: Mohamed Chabi, Mahmoud I. Syam, Sarah Aw

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In Summer 2012, the Foundation Program Unit of Qatar University has started implementing new ways of teaching Math by introducing MML (MyMathLab) as an innovative interactive tool to support standard teaching. In this paper, we focused on the effect of proper use of the Study Plan component of MML on student’s performance. Authors investigated the results of students of pre-calculus course during Fall 2013 in Foundation Program at Qatar University. The results showed that there is a strong correlation between study plan results and final exam results, also a strong relation between homework results and final exam results. In addition, the attendance average affected on the student’s results in general. Multiple regression is determined between passing rate dependent variable and study plan, homework as independent variable.

Keywords: MyMathLab, study plan, assessment, homework, attendance, correlation, regression

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Authors: Saad Bougrine, Salma Ouchraa, Belaid Ahiod, Abdelhakim Ameur El Imrani

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Ant colony optimization is an ant algorithm framework that took inspiration from foraging behaviour of ant colonies. Indeed, ACO algorithms use a chemical communication, represented by pheromone trails, to build good solutions. However, ants involve different communication channels to interact. Thus, this paper introduces the acoustic communication between ants while they are foraging. This process allows fine and local exploration of search space and permits optimal solution to be improved.

Keywords: acoustic communication, ant colony optimization, local search, traveling salesman problem

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Authors: Raninder Kaur Dhillon, Mayur Jethwa, Hardeep Singh Rai

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Information technology has made a pivotal progress across disparate disciplines, one of which is AEC (Architecture, Engineering and Construction) industry. CAD is a form of computer-aided building modulation that architects, engineers and contractors use to create and view two- and three-dimensional models. The AEC industry also uses building information modeling (BIM), a newer computerized modeling system that can create four-dimensional models; this software can greatly increase productivity in the AEC industry. BIM models generate open source IFC (Industry Foundation Classes) files which aim for interoperability for exchanging information throughout the project lifecycle among various disciplines. The methods developed in previous studies require either an IFC schema or MVD and software applications, such as an IFC model server or a Building Information Modeling (BIM) authoring tool, to extract a partial or complete IFC instance model. This paper proposes an efficient algorithm for extracting a partial and total model from an Industry Foundation Classes (IFC) instance model without an IFC schema or a complete IFC model view definition (MVD).

Keywords: BIM, CAD, IFC, MVD

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Authors: S. Bangphan, P. Bangphan, C. Ketsombun, T. Sammana

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Optimization of response surface methodology (RSM) was employed to study the effects of three factor (rubber of clearance, spindle of speed, and rice of moisture) in brown rice peeling machine of the optimal good rice yield (99.67, average of three repeats). The optimized composition derived from RSM regression was analyzed using Regression analysis and Analysis of Variance (ANOVA). At a significant level α=0.05, the values of Regression coefficient, R2 adjust were 96.55% and standard deviation were 1.05056. The independent variables are initial rubber of clearance, spindle of speed and rice of moisture parameters namely. The investigating responses are final rubber clearance, spindle of speed and moisture of rice.

Keywords: brown rice, response surface methodology (RSM), peeling machine, optimization, paddy husker

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Authors: Gaurav Kumar Sinha

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In an era defined by the proliferation of data and the utilization of cloud computing environments, the efficient transfer and processing of big data workloads across multi-cloud platforms have emerged as critical challenges. This research paper embarks on a comprehensive exploration of the complexities associated with managing and optimizing big data in a multi-cloud ecosystem.The foundation of this study is rooted in the recognition that modern enterprises increasingly rely on multiple cloud providers to meet diverse business needs, enhance redundancy, and reduce vendor lock-in. As a consequence, managing data across these heterogeneous cloud environments has become intricate, necessitating innovative approaches to ensure data integrity, security, and performance.The primary objective of this research is to investigate strategies and techniques for enhancing the efficiency of data transfer and processing in multi-cloud scenarios. It recognizes that big data workloads are characterized by their sheer volume, variety, velocity, and complexity, making traditional data management solutions insufficient for harnessing the full potential of multi-cloud architectures.The study commences by elucidating the challenges posed by multi-cloud environments in the context of big data. These challenges encompass data fragmentation, latency, security concerns, and cost optimization. To address these challenges, the research explores a range of methodologies and solutions. One of the key areas of focus is data transfer optimization. The paper delves into techniques for minimizing data movement latency, optimizing bandwidth utilization, and ensuring secure data transmission between different cloud providers. It evaluates the applicability of dedicated data transfer protocols, intelligent data routing algorithms, and edge computing approaches in reducing transfer times.Furthermore, the study examines strategies for efficient data processing across multi-cloud environments. It acknowledges that big data processing requires distributed and parallel computing capabilities that span across cloud boundaries. The research investigates containerization and orchestration technologies, serverless computing models, and interoperability standards that facilitate seamless data processing workflows.Security and data governance are paramount concerns in multi-cloud environments. The paper explores methods for ensuring data security, access control, and compliance with regulatory frameworks. It considers encryption techniques, identity and access management, and auditing mechanisms as essential components of a robust multi-cloud data security strategy.The research also evaluates cost optimization strategies, recognizing that the dynamic nature of multi-cloud pricing models can impact the overall cost of data transfer and processing. It examines approaches for workload placement, resource allocation, and predictive cost modeling to minimize operational expenses while maximizing performance.Moreover, this study provides insights into real-world case studies and best practices adopted by organizations that have successfully navigated the challenges of multi-cloud big data management. It presents a comparative analysis of various multi-cloud management platforms and tools available in the market.

Keywords: multi-cloud environments, big data workloads, data transfer optimization, data processing strategies

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Authors: Y. D. Lim, K. S. Yap, K. T. Ooi

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Cross Vane Expander Compressor (CVEC) is a newly invented expander-compressor combined unit, where it is introduced to replace the compressor and the expansion valve in traditional refrigeration system. The mathematical model of CVEC has been developed to examine its performance, and it was found that the energy consumption of a conventional refrigeration system was reduced by as much as 18%. It is believed that energy consumption can be further reduced by optimizing the device. In this study, the coefficient of performance (COP) of CVEC has been optimized under predetermined operational parameters and constrained main design parameters. Several main design parameters of CVEC were selected to be the variables, and the optimization was done with theoretical model in a simulation program. The theoretical model consists of geometrical model, dynamic model, heat transfer model and valve dynamics model. Complex optimization method, which is a constrained, direct search and multi-variables method was used in the study. As a result, the optimization study suggested that with an appropriate combination of design parameters, a 58% COP improvement in CVEC R134a refrigeration system is possible.

Keywords: COP, cross vane expander-compressor, CVEC, design, simulation, refrigeration system, air-conditioning, R134a, multi variables

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Authors: Ali Ashtiani, Cesar Carrasco

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Accurate determination of thermo-mechanical responses of jointed concrete pavement slabs is essential to implement an effective mechanistic design. Temperature-induced curling of concrete slabs can produce premature top-down cracking in rigid pavements. Curling of concrete slabs can result from daily temperature variation through the slab thickness. The slab curling can also result from temperature gradients due hot weather construction, drying shrinkage and creep that are permanently built into the slabs. The existence of permanent curling implies that concrete slabs are not flat at zero temperature gradient. In this case, slabs may not be in full contact with the underlying base layer when subjecting to traffic. Built-in curling can be a major factor producing loss of slab support. The magnitude of stresses induced in slabs is influenced by the stiffness of the underlying foundation layers and the contact condition along the slab-foundation interface. An approach for finite element modeling of the effect of loss of slab support due to built-in curling is presented in this paper. A series of parametric studies is carried out for a pavement system loaded with a combination of traffic and thermal loads, considering different built-in curling and different foundation rigidities. The results explain the effect of loss of support in the magnitude of stresses produced in concrete slabs. The results of parametric study can also be used to evaluate whether the governing equations that are used to idealize the behavior of jointed concrete pavements and the effect of loss of support have been accurately selected and implemented in the finite element model.

Keywords: built-in curling, finite element modeling, loss of slab support, rigid pavement

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Authors: Tu-Chieh Hung, Wei-Mon Yan, Xiao-Dong Wang, Yu-Xian Huang

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This work employs a combined optimization procedure including a simplified conjugate-gradient method and a three-dimensional fluid flow and heat transfer model to study the optimal geometric parameter design of double-layered microchannel heat sinks. The overall thermal resistance RT is the objective function to be minimized with number of channels, N, the channel width ratio, β, the bottom channel aspect ratio, αb, and upper channel aspect ratio, αu, as the search variables. It is shown that, for the given bottom area (10 mm×10 mm) and heat flux (100 W cm-2), the optimal (minimum) thermal resistance of double-layered microchannel heat sinks is about RT=0.12 ℃/m2W with the corresponding optimal geometric parameters N=73, β=0.50, αb=3.52, and, αu= 7.21 under a constant pumping power of 0.05 W. The optimization process produces a maximum reduction by 52.8% in the overall thermal resistance compared with an initial guess (N=112, β=0.37, αb=10.32 and, αu=10.93). The results also show that the optimal thermal resistance decreases rapidly with the pumping power and tends to be a saturated value afterward. The corresponding optimal values of parameters N, αb, and αu increase while that of β decrease as the pumping power increases. However, further increasing pumping power is not always cost-effective for the application of heat sink designs.

Keywords: optimization, double-layered microchannel heat sink, simplified conjugate-gradient method, thermal resistance

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Authors: K. Karuppasamy

Abstract:

In this paper analysis of an infinite beam resting on multilayer tensionless extensible geosynthetic reinforced granular fill - poor soil system overlying soft soil strata under moving the load with constant velocity is presented. The beam is subjected to a concentrated load moving with constant velocity. The upper reinforced granular bed is modeled by a rough membrane embedded in Pasternak shear layer overlying a series of compressible nonlinear Winkler springs representing the underlying the very poor soil. The multilayer tensionless extensible geosynthetic layer has been assumed to deform such that at the interface the geosynthetic and the soil have some deformation. Nonlinear behavior of granular fill and the very poor soil has been considered in the analysis by means of hyperbolic constitutive relationships. Governing differential equations of the soil foundation system have been obtained and solved with the help of appropriate boundary conditions. The solution has been obtained by employing finite difference method by means of Gauss-Siedel iterative scheme. Detailed parametric study has been conducted to study the influence of various parameters on the response of soil – foundation system under consideration by means of deflection and bending moment in the beam and tension mobilized in the geosynthetic layer. These parameters include the magnitude of applied load, the velocity of the load, damping, the ultimate resistance of the poor soil and granular fill layer. The range of values of parameters has been considered as per Indian Railways conditions. This study clearly observed that the comparisons of multilayer tensionless extensible geosynthetic reinforcement with poor foundation soil and magnitude of applied load, relative compressibility of granular fill and ultimate resistance of poor soil has significant influence on the response of soil – foundation system. However, for the considered range of velocity, the response has been found to be insensitive towards velocity. The ultimate resistance of granular fill layer has also been found to have no significant influence on the response of the system.

Keywords: infinite beams, multilayer tensionless extensible geosynthetic, granular layer, moving load and nonlinear behavior of poor soil

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Authors: Aziza Ben Halima, Julien Bert, Dimitris Visvikis

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In this paper, we propose designing and evaluating a parallel co-manipulated robot dedicated to low-dose-rate prostate brachytherapy. We developed 6 degrees of freedom compact and lightweight robot easy to install in the operating room thanks to its parallel design. This robotic system provides a co-manipulation allowing the surgeon to keep control of the needle’s insertion and consequently to improve the acceptability of the plan for the clinic. The best dimension’s configuration was solved by calculating the geometric model and using an optimization approach. The aim was to ensure the whole coverage of the prostate volume and consider the allowed free space around the patient that includes the ultrasound probe. The final robot dimensions fit in a cube of 300 300 300 mm³. A prototype was 3D printed, and the robot workspace was measured experimentally. The results show that the proposed robotic system satisfies the medical application requirements and permits the needle to reach any point within the prostate.

Keywords: medical robotics, co-manipulation, prostate brachytherapy, optimization

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Authors: Vijaya K. Srivastava, Davide Spinello

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This paper presents performance of two robust gradient-based heuristic optimization procedures based on 3ⁿ enumeration and tunneling approach to seek global optimum of constrained integer problems. Both these procedures consist of two distinct phases for locating the global optimum of integer problems with a linear or non-linear objective function subject to linear or non-linear constraints. In both procedures, in the first phase, a local minimum of the function is found using the gradient approach coupled with hemstitching moves when a constraint is violated in order to return the search to the feasible region. In the second phase, in one optimization procedure, the second sub-procedure examines 3ⁿ integer combinations on the boundary and within hypercube volume encompassing the result neighboring the result from the first phase and in the second optimization procedure a tunneling function is constructed at the local minimum of the first phase so as to find another point on the other side of the barrier where the function value is approximately the same. In the next cycle, the search for the global optimum commences in both optimization procedures again using this new-found point as the starting vector. The search continues and repeated for various step sizes along the function gradient as well as that along the vector normal to the violated constraints until no improvement in optimum value is found. The results from both these proposed optimization methods are presented and compared with one provided by popular MS Excel solver that is provided within MS Office suite and other published results.

Keywords: constrained integer problems, enumerative search algorithm, Heuristic algorithm, Tunneling algorithm

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Authors: Amara Prakasa Rao, N. V. S. N. Sarma

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This paper describes the synthesis of linear array geometry with minimum sidelobe level and null control using the Taguchi method. Based on the concept of the orthogonal array, Taguchi method effectively reduces the number of tests required in an optimization process. Taguchi method has been successfully applied in many fields such as mechanical, chemical engineering, power electronics, etc. Compared to other evolutionary methods such as genetic algorithms, simulated annealing and particle swarm optimization, the Taguchi method is much easier to understand and implement. It requires less computational/iteration processing to optimize the problem. Different cases are considered to illustrate the performance of this technique. Simulation results show that this method outperforms the other evolution algorithms (like GA, PSO) for smart antenna systems design.

Keywords: array factor, beamforming, null placement, optimization method, orthogonal array, Taguchi method, smart antenna system

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Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

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In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

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Authors: Santosh Kumar Suman, Vinod Kumar Giri

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The goal of this paper is to outline a speed controller of a DC motor by choice of a PID parameters utilizing genetic algorithms (GAs), the DC motor is extensively utilized as a part of numerous applications such as steel plants, electric trains, cranes and a great deal more. DC motor could be represented by a nonlinear model when nonlinearities such as attractive dissemination are considered. To provide effective control, nonlinearities and uncertainties in the model must be taken into account in the control design. The DC motor is considered as third order system. Objective of this paper three type of tuning techniques for PID parameter. In this paper, an independently energized DC motor utilizing MATLAB displaying, has been outlined whose velocity might be examined utilizing the Proportional, Integral, Derivative (KP, KI , KD) addition of the PID controller. Since, established controllers PID are neglecting to control the drive when weight parameters be likewise changed. The principle point of this paper is to dissect the execution of optimization techniques viz. The Genetic Algorithm (GA) for improve PID controllers parameters for velocity control of DC motor and list their points of interest over the traditional tuning strategies. The outcomes got from GA calculations were contrasted and that got from traditional technique. It was found that the optimization techniques beat customary tuning practices of ordinary PID controllers.

Keywords: DC motor, PID controller, optimization techniques, genetic algorithm (GA), objective function, IAE

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Authors: Jai Heui Kim, Sotheara Veng

Abstract:

This paper studies the portfolio optimization problem for a pension fund under a hybrid model of stochastic volatility and constant elasticity of variance (CEV) using asymptotic analysis method. When the volatility component is fast mean-reverting, it is able to derive asymptotic approximations for the value function and the optimal strategy for general utility functions. Explicit solutions are given for the exponential and hyperbolic absolute risk aversion (HARA) utility functions. The study also shows that using the leading order optimal strategy results in the value function, not only up to the leading order, but also up to first order correction term. A practical strategy that does not depend on the unobservable volatility level is suggested. The result is an extension of the Merton's solution when stochastic volatility and elasticity of variance are considered simultaneously.

Keywords: asymptotic analysis, constant elasticity of variance, portfolio optimization, stochastic optimal control, stochastic volatility

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Authors: Somayeh Komeylian

Abstract:

The direction of arrival (DoA) estimation is the crucial aspect of the radar technologies for detecting and dividing several signal sources. In this scenario, the antenna array output modeling involves numerous parameters including noise samples, signal waveform, signal directions, signal number, and signal to noise ratio (SNR), and thereby the methods of the DoA estimation rely heavily on the generalization characteristic for establishing a large number of the training data sets. Hence, we have analogously represented the two different optimization models of the DoA estimation; (1) the implementation of the decision directed acyclic graph (DDAG) for the multiclass least-squares support vector machine (LS-SVM), and (2) the optimization method of the deep neural network (DNN) radial basis function (RBF). We have rigorously verified that the LS-SVM DDAG algorithm is capable of accurately classifying DoAs for the three classes. However, the accuracy and robustness of the DoA estimation are still highly sensitive to technological imperfections of the antenna arrays such as non-ideal array design and manufacture, array implementation, mutual coupling effect, and background radiation and thereby the method may fail in representing high precision for the DoA estimation. Therefore, this work has a further contribution on developing the DNN-RBF model for the DoA estimation for overcoming the limitations of the non-parametric and data-driven methods in terms of array imperfection and generalization. The numerical results of implementing the DNN-RBF model have confirmed the better performance of the DoA estimation compared with the LS-SVM algorithm. Consequently, we have analogously evaluated the performance of utilizing the two aforementioned optimization methods for the DoA estimation using the concept of the mean squared error (MSE).

Keywords: DoA estimation, Adaptive antenna array, Deep Neural Network, LS-SVM optimization model, Radial basis function, and MSE

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Authors: Kittipob Kondee, Chutima Prommak

Abstract:

In this paper, we propose an optimization technique that can be used to optimize the placements of reference nodes and improve the location determination performance for the multi-floor building. The proposed technique is based on Simulated Annealing algorithm (SA) and is called MSMR-M. The performance study in this work is based on simulation. We compare other node-placement techniques found in the literature with the optimal node-placement solutions obtained from our optimization. The results show that using the optimal node-placement obtained by our proposed technique can improve the positioning error distances up to 20% better than those of the other techniques. The proposed technique can provide an average error distance within 1.42 meters.

Keywords: indoor positioning system, optimization system design, multi-floor building, wireless sensor networks

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Authors: N. Jinesh, K. Shankar

Abstract:

This article presents a method of using the one dimensional piezo-electric patch on beam model for structural identification. A hybrid element constituted of one dimensional beam element and a PZT sensor is used with reduced material properties. This model is convenient and simple for identification of beams. Accuracy of this element is first verified against a corresponding 3D finite element model (FEM). The structural identification is carried out as an inverse problem whereby parameters are identified by minimizing the deviation between the predicted and measured voltage response of the patch, when subjected to excitation. A non-classical optimization algorithm Particle Swarm Optimization is used to minimize this objective function. The signals are polluted with 5% Gaussian noise to simulate experimental noise. The proposed method is applied on beam structure and identified parameters are stiffness and damping. The model is also validated experimentally.

Keywords: inverse problem, particle swarm optimization, PZT patches, structural identification

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Authors: Medani Khaled Ben Oualid

Abstract:

Most of researchers solved and analyzed the ORPD problem in the normal conditions. However, network collapses appear in contingency conditions. In this paper, ORPD under several contingencies is presented using the proposed method WOA. To ensure viability of the power system in contingency conditions, several critical cases are simulated in order to prevent and prepare the power system to face such situations. The results obtained are carried out in IEEE 30 bus test system for the solution of ORPD problem in which control of bus voltages, tap position of transformers and reactive power sources are involved. Moreover, another method, namely, Particle Swarm Optimization with Time Varying Acceleration Coefficient (PSO-TVAC) has been compared with the proposed technique. Simulation results indicate that the proposed WOA gives remarkable solution in terms of effectiveness in case of outages.

Keywords: optimal reactive power dispatch, metaheuristic techniques, whale optimization algorithm, real power loss minimization, contingency conditions

Procedia PDF Downloads 83