Search results for: Design Optimization

Authors: Dimitrios J. Dimitriou

Abstract:

Airport’s serving a tourist destination are an essential counterpart of the tourist demand supply chain, and their productivity is related to the region’s attractiveness and is enhanced by the air transport business. In this paper, the evaluation framework of the scheduled flights between two tourist airports is taken into consideration. By adopting a systemic approach, the arrivals from an airport that its connectivity heavily depended on the departures of another major airport are reviewed. The methodology framework, based on inventory control theory and the numerical example, promotes the use of the modelling formulation. The results would be essential for comparison and exercising to other similar cases.

Keywords: Airport connectivity, inventory control, optimization, optimum allocation.

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Authors: Meng Wu

Abstract:

Motion planning is a common task required to be fulfilled by robots. A strategy combining Ant Colony Optimization (ACO) and gravity gradient inversion algorithm is proposed for motion planning of mobile robots. In this paper, in order to realize optimal motion planning strategy, the cost function in ACO is designed based on gravity gradient inversion algorithm. The obstacles around mobile robot can cause gravity gradient anomalies; the gradiometer is installed on the mobile robot to detect the gravity gradient anomalies. After obtaining the anomalies, gravity gradient inversion algorithm is employed to calculate relative distance and orientation between mobile robot and obstacles. The relative distance and orientation deduced from gravity gradient inversion algorithm is employed as cost function in ACO algorithm to realize motion planning. The proposed strategy is validated by the simulation and experiment results.

Keywords: Motion planning, gravity gradient inversion algorithm, ant colony optimization.

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Authors: Jehad Al Dallal

Abstract:

Software engineers apply different measures to quantify the quality of software design. These measures consider artifacts developed at low or high level software design phases. The results are used to point to design weaknesses and to indicate design points that have to be restructured. Understanding the relationship among the quality measures and among the design quality aspects considered by these measures is important to interpreting the impact of a measure for a quality aspect on other potentially related aspects. In addition, exploring the relationship between quality measures helps to explain the impact of different quality measures on external quality aspects, such as reliability and maintainability. In this paper, we report a replication study that empirically explores the correlation between six well known and commonly applied design quality measures. These measures consider several quality aspects, including complexity, cohesion, coupling, and inheritance. The results indicate that inheritance measures are weakly correlated to other measures, whereas complexity, coupling, and cohesion measures are mostly strongly correlated.  

Keywords: Quality attribute, quality measure, software design quality, spearman correlation.

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Authors: Chan-Sik Kim, Jong-Seong Kim, Se Won Lee, Hoo-Gon Choi

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In rapidly changing market environment, firms are investing a lot of time and resources into new product development (NPD) projects to make profit and to obtain competitive advantage. However, failure rate of NPD projects is becoming high due to various internal and external risks which hinder successful NPD projects. To reduce the failure rate, it is critical that risks have to be managed effectively and efficiently through good strategy, and treated by optimal responses to minimize risk cost. Four strategies are adopted to handle the risks in this study. The optimal responses are characterized by high reduction of risk costs with high efficiency. This study suggests a framework to decide the optimal responses considering the core risks, risk costs, response efficiency and response costs for successful NPD projects. Both binary particles warm optimization (BPSO) and multi-objective particle swarm optimization (MOPSO) methods are mainly used in the framework. Although several limitations exist in use for real industries, the frame work shows good strength for handling the risks with highly scientific ways through an example.

Keywords: NPD projects, risk cost, strategy, optimal responses, Particle Swarm Optimization.

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Authors: Ahmad Yame, Ahad Ali, Badih Jawad, Daw Al-Werfalli Mohamed Nasser, Sabah Abro

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Industries in general have a lot of waste. Wool textile company, Baniwalid, Libya has many complex problems that led to enormous waste generated due to the lack of lean strategies, expertise, technical support and commitment. To successfully address waste at wool textile company, this study will attempt to develop a methodical approach that integrates lean manufacturing tools to optimize performance characteristics such as lead time and delivery. This methodology will utilize Value Stream Mapping (VSM) techniques to identify the process variables that affect production. Once these variables are identified, Design of Experiments (DOE) Methodology will be used to determine the significantly influential process variables, these variables are then controlled and set at their optimal to achieve optimal levels of productivity, quality, agility, efficiency and delivery to analyze the outputs of the simulation model for different lean configurations. The goal of this research is to investigate how the tools of lean manufacturing can be adapted from the discrete to the continuous manufacturing environment and to evaluate their benefits at a specific industrial.

Keywords: Lean manufacturing, DOE, value stream mapping, textiles.

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Authors: Palang Wongtanasuporn

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Rural villagers in Thailand have unique skill for producing craft using local materials. However, the appearance and function of their products are not suited to the demand of international market. The Thai government policy on sustainable economy emphasises the necessity to incorporate a design strategy that will draw out the unique qualities and add value to the products, while raising the satisfaction of international consumer. As an industrial designer, the author sees opportunities that design can enhance sustainability of Thai local products through the potentials that available in village-based enterprises. This research attempts to address, how best use design to practically solve the problems in the development of Thais product in. The privilege solution is expressed through the design of design strategy that supports sustain economic development of microenterprise in Thailand in the way that aligns with product design development. This consideration integrates together with global business outlook in the development of products from rural communities.

Keywords: Community Development, Sufficiency Economy Philosophy, Product Design, Strategy Management.

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Authors: Ulrike Völlinger, Erik Lehmann, Rainer Stark

Abstract:

The intention of this paper is, to help the user of evolutionary algorithms to adapt them easier to their problem at hand. For a lot of problems in the technical field it is not necessary to reach an optimum solution, but to reach a good solution in time. In many cases the solution is undetermined or there doesn-t exist a method to determine the solution. For these cases an evolutionary algorithm can be useful. This paper intents to give the user rules of thumb with which it is easier to decide if the problem is suitable for an evolutionary algorithm and how to design them.

Keywords: Multi criteria optimization, Memetic algorithms

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Authors: Peyman Honarmandi, Mazen Alhirsh

Abstract:

Banner towing is a major form of advertisement. It consists of a banner showing a logo or a selection of words or letters being towed by an aircraft. Traditionally bush planes have been used to tow banners given their high thrust capabilities, however, with the development of Remote-Controlled (RC) aircraft, they could be a good replacement as RC planes mitigate the risk of human life and can be easier to operate. This paper studies the best banner design to be towed by an RC aircraft. This is done by conducting wind tunnel testing on an array of banners with different materials and designs. A pull gauge is used to record the drag force during testing which is then used to calculate the coefficient of drag, Cd. The testing results show that the best banner design would be a hybrid design with a solid and mesh material. The design with the lowest Cd of 0.082 was a half ripstop nylon half polyester mesh design. On the other hand, the design with highest Cd of 0.305 involved incorporating a tail chute to decrease fluttering.

Keywords: Aerodynamics of banner, banner design, banner towing, drag coefficients of banner, RC aircraft banner.

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Authors: M. Rajasimman, K. Murugaiyan

Abstract:

In this work, sorption of nickel from aqueous solution on hypnea valentiae, red macro algae, was investigated. Batch experiments have been carried out to find the effect of various parameters such as pH, temperature, sorbent dosage, metal concentration and contact time on the sorption of nickel using hypnea valentiae. Response surface methodology (RSM) is employed to optimize the process parameters. Based on the central composite design, quadratic model was developed to correlate the process variables to the response. The most influential factor on each experimental design response was identified from the analysis of variance (ANOVA). The optimum conditions for the sorption of nickel were found to be: pH – 5.1, temperature – 36.8oC, sorbent dosage – 5.1 g/L, metal concentration – 100 mg/L and contact time – 30 min. At these optimized conditions the maximum removal of nickel was found to be 91.97%. A coefficient of determination R2 value 0.9548 shows the fitness of response surface methodology in this work.

Keywords: Optimization, metal, Hypnea valentia, response surface methodology, red algae.

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Authors: Wann-Ming Wey

Abstract:

The link between urban planning and design principles and the built environment of an urban renewal area is of interest to the field of urban studies. During the past decade, there has also been increasing interest in urban planning and design; this interest is motivated by the possibility that design policies associated with the built environment can be used to control, manage, and shape individual activity and behavior. However, direct assessments and design techniques of the links between how urban planning design policies influence individuals are still rare in the field. Recent research efforts in urban design have focused on the idea that land use and design policies can be used to increase the quality of design projects for an urban renewal area-s built environment. The development of appropriate design techniques for the built environment is an essential element of this research. Quality function deployment (QFD) is a powerful tool for improving alternative urban design and quality for urban renewal areas, and for procuring a citizen-driven quality system. In this research, we propose an integrated framework based on QFD and an Analytic Network Process (ANP) approach to determine the Alternative Technical Requirements (ATRs) to be considered in designing an urban renewal planning and design alternative. We also identify the research designs and methodologies that can be used to evaluate the performance of urban built environment projects. An application in an urban renewal built environment planning and design project evaluation is presented to illustrate the proposed framework.

Keywords: Analytic Network Process, Built Environment, Quality Function Deployment, Urban Design, Urban Renewal.

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

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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: Chang, Chun-Lang, Liu, Chun-Kai

Abstract:

This study, for its research subjects, uses patients who had undergone total knee replacement surgery from the database of the National Health Insurance Administration. Through the review of literatures and the interviews with physicians, important factors are selected after careful screening. Then using Cross Entropy Method, Genetic Algorithm Logistic Regression, and Particle Swarm Optimization, the weight of each factor is calculated and obtained. In the meantime, Excel VBA and Case Based Reasoning are combined and adopted to evaluate the system. Results show no significant difference found through Genetic Algorithm Logistic Regression and Particle Swarm Optimization with over 97% accuracy in both methods. Both ROC areas are above 0.87. This study can provide critical reference to medical personnel as clinical assessment to effectively enhance medical care quality and efficiency, prevent unnecessary waste, and provide practical advantages to resource allocation to medical institutes.

Keywords: Total knee replacement, Case Based Reasoning, Cross Entropy Method, Genetic Algorithm Logistic Regression, Particle Swarm Optimization.

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Authors: Somsri Binraman, Boonliang Kaewnapan, Krittika Tanprasert

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In the package design industry, there are a lot of tacit knowledge resided within each designer. The objectives are to capture them and compile it to be used as a teaching resource and to create a video clip of package design process as well as to evaluate its quality and learning effectiveness. Interview were used as a technique for capturing knowledge in brand design concept, differentiation, recognition, rank of recognition factor, consumer survey, knowledge about marketing, research, graphic design, the effect of color, and law and regulation. Video clip about package design were created. The clip consisted of both the speech and clip of actual process. The quality of the video in term of media was ranked as good while the content was ranked as excellent. The students- score on post-test was significantly greater than that of pretest (p>0.001).

Keywords: Tacit knowledge, interview, video, packaging, design.

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Authors: A. Danbaba

Abstract:

Samurai Sudoku consists of five Sudoku square designs each having nine treatments in each row (column or sub-block) only once such the five Sudoku designs overlaps. Two or more Samurai designs can be joint together to give an extended Samurai design. In addition, two Samurai designs, each containing five Sudoku square designs, are mutually orthogonal (Graeco). If we superimpose two Samurai designs and obtained a pair of Latin and Greek letters in each row (column or sub-block) of the five Sudoku designs only once, then we have Graeco Samurai design. In this paper, simple method of constructing Samurai designs and mutually orthogonal Samurai design are proposed. In addition, linear models and methods of data analysis for the designs are proposed.

Keywords: Samurai design, Graeco samurai design, sudoku design, row or column swap.

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Authors: S. Esfandeh, M. Sedighizadeh

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Weather systems use enormously complex combinations of numerical tools for study and forecasting. Unfortunately, due to phenomena in the world climate, such as the greenhouse effect, classical models may become insufficient mostly because they lack adaptation. Therefore, the weather forecast problem is matched for heuristic approaches, such as Evolutionary Algorithms. Experimentation with heuristic methods like Particle Swarm Optimization (PSO) algorithm can lead to the development of new insights or promising models that can be fine tuned with more focused techniques. This paper describes a PSO approach for analysis and prediction of data and provides experimental results of the aforementioned method on realworld meteorological time series.

Keywords: Weather, Climate, PSO, Prediction, Meteorological

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Authors: Nickolay Jelev, Andy Keane, Carren Holden, András Sóbester

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In aircraft design, the jump from the conceptual to preliminary design stage introduces a level of complexity which cannot be realistically handled by a single optimiser, be that a human (chief engineer) or an algorithm. The design process is often partitioned along disciplinary lines, with each discipline given a level of autonomy. This introduces a number of challenges including, but not limited to: coupling of design variables; coordinating disciplinary teams; handling of large amounts of analysis data; reaching an acceptable design within time constraints. A number of classical Multidisciplinary Design Optimisation (MDO) architectures exist in academia specifically designed to address these challenges. Their limited use in the industrial aircraft design process has inspired the authors of this paper to develop an alternative strategy based on well established ideas from Decision Support Systems. The proposed rule based architecture sacrifices possibly elusive guarantees of convergence for an attractive return in simplicity. The method is demonstrated on analytical and aircraft design test cases and its performance is compared to a number of classical distributed MDO architectures.

Keywords: Multidisciplinary design optimisation, rule based architecture, aircraft design, decision support system.

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Authors: Ishtiaq Ahmed, Muhammad Anjum Zia, Hafiz Muhammad Nasir Iqbal

Abstract:

The purpose of the present work was to study the production and process parameters optimization for the synthesis of cellulase from Trichoderma viride in solid state fermentation (SSF) using an agricultural wheat straw as substrates; as fungal conversion of lignocellulosic biomass for cellulase production is one among the major increasing demand for various biotechnological applications. An optimization of process parameters is a necessary step to get higher yield of product. Several kinetic parameters like pretreatment, extraction solvent, substrate concentration, initial moisture content, pH, incubation temperature and inoculum size were optimized for enhanced production of third most demanded industrially important cellulase. The maximum cellulase enzyme activity 398.10±2.43 μM/mL/min was achieved when proximally analyzed lignocellulosic substrate wheat straw inocubated at 2% HCl as pretreatment tool along with distilled water as extraction solvent, 3% substrate concentration 40% moisture content with optimum pH 5.5 at 45°C incubation temperature and 10% inoculum size.

Keywords: Cellulase, Lignocellulosic residue, Processoptimization, Proximal analysis, SSF, Trichoderma viride.

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Authors: C. Chitra, P. Subbaraj

Abstract:

The shortest path routing problem is a multiobjective nonlinear optimization problem with constraints. This problem has been addressed by considering Quality of service parameters, delay and cost objectives separately or as a weighted sum of both objectives. Multiobjective evolutionary algorithms can find multiple pareto-optimal solutions in one single run and this ability makes them attractive for solving problems with multiple and conflicting objectives. This paper uses an elitist multiobjective evolutionary algorithm based on the Non-dominated Sorting Genetic Algorithm (NSGA), for solving the dynamic shortest path routing problem in computer networks. A priority-based encoding scheme is proposed for population initialization. Elitism ensures that the best solution does not deteriorate in the next generations. Results for a sample test network have been presented to demonstrate the capabilities of the proposed approach to generate well-distributed pareto-optimal solutions of dynamic routing problem in one single run. The results obtained by NSGA are compared with single objective weighting factor method for which Genetic Algorithm (GA) was applied.

Keywords: Multiobjective optimization, Non-dominated SortingGenetic Algorithm, Routing, Weighted sum.

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Authors: Kwang Y. Lee, Tae R. Park, Jae C. Kwak, Yong S. Koo

Abstract:

When a small H/W IP is designed, we can develop an appropriate verification environment by observing the simulated signal waves, or using the serial test vectors for the fixed output. In the case of design and verification of a massive parallel processor with multiple IPs, it-s difficult to make a verification system with existing common verification environment, and to verify each partial IP. A TestDrive verification environment can build easy and reliable verification system that can produce highly intuitive results by applying Modelsim and SystemVerilog-s DPI. It shows many advantages, for example a high-level design of a GPGPU processor design can be migrate to FPGA board immediately.

Keywords: Virtual Simulation, Verification, IP Design, GPGPU

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Authors: R. Rajeshkannan, M. Rajasimman, N. Rajamohan

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In this study, the sorption of Malachite green (MG) on Hydrilla verticillata biomass, a submerged aquatic plant, was investigated in a batch system. The effects of operating parameters such as temperature, adsorbent dosage, contact time, adsorbent size, and agitation speed on the sorption of Malachite green were analyzed using response surface methodology (RSM). The proposed quadratic model for central composite design (CCD) fitted very well to the experimental data that it could be used to navigate the design space according to ANOVA results. The optimum sorption conditions were determined as temperature - 43.5oC, adsorbent dosage - 0.26g, contact time - 200min, adsorbent size - 0.205mm (65mesh), and agitation speed - 230rpm. The Langmuir and Freundlich isotherm models were applied to the equilibrium data. The maximum monolayer coverage capacity of Hydrilla verticillata biomass for MG was found to be 91.97 mg/g at an initial pH 8.0 indicating that the optimum sorption initial pH. The external and intra particle diffusion models were also applied to sorption data of Hydrilla verticillata biomass with MG, and it was found that both the external diffusion as well as intra particle diffusion contributes to the actual sorption process. The pseudo-second order kinetic model described the MG sorption process with a good fitting.

Keywords: Response surface methodology, Hydrilla verticillata, malachite green, adsorption, central composite design

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Authors: Hassan Zarei, Ali Vahidian Kamyad, Sohrab Effati

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In this paper, a mathematical model of human immunodeficiency virus (HIV) is utilized and an optimization problem is proposed, with the final goal of implementing an optimal 900-day structured treatment interruption (STI) protocol. Two type of commonly used drugs in highly active antiretroviral therapy (HAART), reverse transcriptase inhibitors (RTI) and protease inhibitors (PI), are considered. In order to solving the proposed optimization problem an adaptive memetic algorithm with population management (AMAPM) is proposed. The AMAPM uses a distance measure to control the diversity of population in genotype space and thus preventing the stagnation and premature convergence. Moreover, the AMAPM uses diversity parameter in phenotype space to dynamically set the population size and the number of crossovers during the search process. Three crossover operators diversify the population, simultaneously. The progresses of crossover operators are utilized to set the number of each crossover per generation. In order to escaping the local optima and introducing the new search directions toward the global optima, two local searchers assist the evolutionary process. In contrast to traditional memetic algorithms, the activation of these local searchers is not random and depends on both the diversity parameters in genotype space and phenotype space. The capability of AMAPM in finding optimal solutions compared with three popular metaheurestics is introduced.

Keywords: HIV therapy design, memetic algorithms, adaptivealgorithms, nonlinear integer programming.

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Authors: E.Sasikumar, T.Viruthagiri

Abstract:

Simultaneous Saccharification and Fermentation (SSF) of sugarcane bagasse by cellulase and Pachysolen tannophilus MTCC *1077 were investigated in the present study. Important process variables for ethanol production form pretreated bagasse were optimized using Response Surface Methodology (RSM) based on central composite design (CCD) experiments. A 23 five level CCD experiments with central and axial points was used to develop a statistical model for the optimization of process variables such as incubation temperature (25–45°) X1, pH (5.0–7.0) X2 and fermentation time (24–120 h) X3. Data obtained from RSM on ethanol production were subjected to the analysis of variance (ANOVA) and analyzed using a second order polynomial equation and contour plots were used to study the interactions among three relevant variables of the fermentation process. The fermentation experiments were carried out using an online monitored modular fermenter 2L capacity. The processing parameters setup for reaching a maximum response for ethanol production was obtained when applying the optimum values for temperature (32°C), pH (5.6) and fermentation time (110 h). Maximum ethanol concentration (3.36 g/l) was obtained from 50 g/l pretreated sugarcane bagasse at the optimized process conditions in aerobic batch fermentation. Kinetic models such as Monod, Modified Logistic model, Modified Logistic incorporated Leudeking – Piret model and Modified Logistic incorporated Modified Leudeking – Piret model have been evaluated and the constants were predicted.

Keywords: Sugarcane bagasse, ethanol, optimization, Pachysolen tannophilus.

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Authors: Mhand Hifi, Hedi Mhalla, Mustapha Michaphy

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In this paper, we study the multi-scenario knapsack problem, a variant of the well-known NP-Hard single knapsack problem. We investigate the use of an adaptive algorithm for solving heuristically the problem. The used method combines two complementary phases: a size reduction phase and a dynamic 2- opt procedure one. First, the reduction phase applies a polynomial reduction strategy; that is used for reducing the size problem. Second, the adaptive search procedure is applied in order to attain a feasible solution Finally, the performances of two versions of the proposed algorithm are evaluated on a set of randomly generated instances.

Keywords: combinatorial optimization, max-min optimization, knapsack, heuristics, problem reduction

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Authors: Tien-Tung Chung, Chin-Te Lin, Chung-Yun Lee, Kuang-Chao Fan, Shou-Heng Chen

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This paper studies the optimum design for reducing optical loss of an 8x8 mechanical type optical switch due to the temperature change. The 8x8 optical switch is composed of a base, 8 input fibers, 8 output fibers, 3 fixed mirrors and 17 movable mirrors. First, an innovative switch configuration is proposed with thermal-compensated design. Most mechanical type optical switches have a disadvantage that their precision and accuracy are influenced by the ambient temperature. Therefore, the thermal-compensated design is to deal with this situation by using materials with different thermal expansion coefficients (α). Second, a parametric modeling program is developed to generate solid models for finite element analysis, and the thermal and structural behaviors of the switch are analyzed. Finally, an integrated optimum design program, combining Autodesk Inventor Professional software, finite element analysis software, and genetic algorithms, is developed for improving the thermal behaviors that the optical loss of the switch is reduced. By changing design parameters of the switch in the integrated design program, the final optimum design that satisfies the design constraints and specifications can be found.

Keywords: Optical switch, finite element analysis, thermal-compensated design, optimum design.

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Authors: Mei Shan Ngan, Chee Wei Tan

Abstract:

Due to the non-linear characteristics of photovoltaic (PV) array, PV systems typically are equipped with the capability of maximum power point tracking (MPPT) feature. Moreover, in the case of PV array under partially shaded conditions, hotspot problem will occur which could damage the PV cells. Partial shading causes multiple peaks in the P-V characteristic curves. This paper presents a hybrid algorithm of Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN) MPPT algorithm for the detection of global peak among the multiple peaks in order to extract the true maximum energy from PV panel. The PV system consists of PV array, dc-dc boost converter controlled by the proposed MPPT algorithm and a resistive load. The system was simulated using MATLAB/Simulink package. The simulation results show that the proposed algorithm performs well to detect the true global peak power. The results of the simulations are analyzed and discussed.

Keywords: Photovoltaic (PV), Partial Shading, Maximum Power Point Tracking (MPPT), Particle Swarm Optimization (PSO) and Artificial Neural Network (ANN)

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Authors: B.Bahmani Firouzi, T. Niknam, M. Nayeripour

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Clustering is a very well known technique in data mining. One of the most widely used clustering techniques is the kmeans algorithm. Solutions obtained from this technique depend on the initialization of cluster centers and the final solution converges to local minima. In order to overcome K-means algorithm shortcomings, this paper proposes a hybrid evolutionary algorithm based on the combination of PSO, SA and K-means algorithms, called PSO-SA-K, which can find better cluster partition. The performance is evaluated through several benchmark data sets. The simulation results show that the proposed algorithm outperforms previous approaches, such as PSO, SA and K-means for partitional clustering problem.

Keywords: Data clustering, Hybrid evolutionary optimization algorithm, K-means algorithm, Simulated Annealing (SA), Particle Swarm Optimization (PSO).

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Authors: Gaoyuan Wang, Tian Chen, Junnan Liu

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Facing a period of major change that is rarely seen in a century, China formulates the 14th Five-Year Plan and places emphasis on promoting high-quality development. In this context, the overall urban design has become a crucial and systematic tool for high-quality urban development. However, there are bottlenecks in the cognition of nature, content scope and transmission mechanisms of the current overall urban design in China. The paper interprets the emerging demands of the 14th Five-Year Plan on urban design in terms of new value-quality priority, new dynamic-space performance, new target-region coordination and new path-refined governance. Based on the new trend and appeal, the multi-dimensional thinking integrated with the major tasks of urban design are proposed accordingly, which is the biomass thinking in ecological, production and living element, the strategic thinking in spatial structure, the systematic thinking in the cityscape, the low-carbon thinking in urban form, the governance thinking in public space, the user thinking in design implementation. The paper explores the possibility of transforming the value thinking and technical system of urban design in China and provides a breakthrough path for the urban planning and design industry to better respond to the propositions of the country’s 14th Five-Year Plan.

Keywords: China’s 14th five-year plan, overall urban design, urban design thinking, transformation of urban design.

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Authors: Mahdi Pirmoradian, Olayinka Adigun, Christos Politis

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Cooperative spectrum sensing is a crucial challenge in cognitive radio networks. Cooperative sensing can increase the reliability of spectrum hole detection, optimize sensing time and reduce delay in cooperative networks. In this paper, an efficient central capacity optimization algorithm is proposed to minimize cooperative sensing time in a homogenous sensor network using OR decision rule subject to the detection and false alarm probabilities constraints. The evaluation results reveal significant improvement in the sensing time and normalized capacity of the cognitive sensors.

Keywords: Cooperative networks, normalized capacity, sensing time.

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Authors: Konstantinos Metaxiotis, Konstantinos Liagkouras

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The objective of this study is to examine the performance of three well-known multiobjective evolutionary algorithms for solving optimization problems. The first algorithm is the Non-dominated Sorting Genetic Algorithm-II (NSGA-II), the second one is the Strength Pareto Evolutionary Algorithm 2 (SPEA-2), and the third one is the Multiobjective Evolutionary Algorithms based on decomposition (MOEA/D). The examined multiobjective algorithms are analyzed and tested on the ZDT set of test functions by three performance metrics. The results indicate that the NSGA-II performs better than the other two algorithms based on three performance metrics.

Keywords: MOEAs, Multiobjective optimization, ZDT test functions, performance metrics.

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Authors: Zeshan Ahmad, Matteo Zoppi, Rezia Molfino

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The stiffness of the workpiece is very important to reduce the errors in manufacturing process. The high stiffness of the workpiece can be achieved by optimal positioning of fixture elements in the fixture. The minimization of the sum of the nodal deflection normal to the surface is used as objective function in previous research. The deflection in other direction has been neglected. The 3-2-1 fixturing principle is not valid for metal sheets due to its flexible nature. We propose a new fixture layout optimization method N-3-2-1 for metal sheets that uses the strain energy of the finite elements. This method combines the genetic algorithm and finite element analysis. The objective function in this method is to minimize the sum of all the element strain energy. By using the concept of element strain energy, the deformations in all the directions have been considered. Strain energy and stiffness are inversely proportional to each other. So, lower the value of strain energy, higher will be the stiffness. Two different kinds of case studies are presented. The case studies are solved for both objective functions; element strain energy and nodal deflection. The result are compared to verify the propose method.

Keywords: Fixture layout, optimization, fixturing element, genetic algorithm.

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