Search results for: product optimization

Authors: Gaohuizi Guo, Ning Zhang

Abstract:

Firefly algorithm (FA) and Sine Cosine algorithm (SCA) are two very popular and advanced metaheuristic algorithms. However, these algorithms applied to multi-objective optimization problems have some shortcomings, respectively, such as premature convergence and limited exploration capability. Combining the privileges of FA and SCA while avoiding their deficiencies may improve the accuracy and efficiency of the algorithm. This paper proposes a hybridization of FA and SCA algorithms, named multi-objective firefly-sine cosine algorithm (MFA-SCA), to develop a more efficient meta-heuristic algorithm than FA and SCA.

Keywords: Firefly algorithm, hybrid algorithm, multi-objective optimization, Sine Cosine algorithm.

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Authors: Hadi Khosravi Farsani, Mohammadali Nematbakhsh

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To overcome the product overload of Internet shoppers, we introduce a semantic recommendation procedure which is more efficient when applied to Internet shopping malls. The suggested procedure recommends the semantic products to the customers and is originally based on Web usage mining, product classification, association rule mining, and frequently purchasing. We applied the procedure to the data set of MovieLens Company for performance evaluation, and some experimental results are provided. The experimental results have shown superior performance in terms of coverage and precision.

Keywords: Personalization, Recommendation, OWL Ontology, Electronic Catalogs, Classification.

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Authors: Daniel Kostrzewa, Henryk Josiński

Abstract:

The expanded Invasive Weed Optimization algorithm (exIWO) is an optimization metaheuristic modelled on the original IWO version created by the researchers from the University of Tehran. The authors of the present paper have extended the exIWO algorithm introducing a set of both deterministic and non-deterministic strategies of individuals’ selection. The goal of the project was to evaluate the exIWO by testing its usefulness for solving some test instances of the traveling salesman problem (TSP) taken from the TSPLIB collection which allows comparing the experimental results with optimal values.

Keywords: Expanded Invasive Weed Optimization algorithm (exIWO), Traveling Salesman Problem (TSP), heuristic approach, inversion operator.

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Authors: Y. K. Lin, H. T. Hsieh, F. Y. Hsieh

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Total weighted tardiness is a measure of customer satisfaction. Minimizing it represents satisfying the general requirement of on-time delivery. In this research, we consider an ant colony optimization (ACO) algorithm to solve the problem of scheduling unrelated parallel machines to minimize total weighted tardiness. The problem is NP-hard in the strong sense. Computational results show that the proposed ACO algorithm is giving promising results compared to other existing algorithms.

Keywords: ant colony optimization, total weighted tardiness, unrelated parallel machines.

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Authors: Broderick Crawford, Ricardo Soto, Natalia Berrios, Eduardo Olguin

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In this paper, we present a binary cat swarm optimization for solving the Set covering problem. The set covering problem is a well-known NP-hard problem with many practical applications, including those involving scheduling, production planning and location problems. Binary cat swarm optimization is a recent swarm metaheuristic technique based on the behavior of discrete cats. Domestic cats show the ability to hunt and are curious about moving objects. The cats have two modes of behavior: seeking mode and tracing mode. We illustrate this approach with 65 instances of the problem from the OR-Library. Moreover, we solve this problem with 40 new binarization techniques and we select the technical with the best results obtained. Finally, we make a comparison between results obtained in previous studies and the new binarization technique, that is, with roulette wheel as transfer function and V3 as discretization technique.

Keywords: Binary cat swarm optimization, set covering problem, metaheuristic, binarization methods.

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Authors: M. H. Moradi, S. M. Moosavi, A. R. Reisi

Abstract:

The main objective of this paper is to investigate the enhancement of power system stability via coordinated tuning of Power System Stabilizers (PSSs) in a multi-machine power system. The design problem of the proposed controllers is formulated as an optimization problem. Chaotic catfish particle swarm optimization (C-Catfish PSO) algorithm is used to minimize the ITAE objective function. The proposed algorithm is evaluated on a two-area, 4- machines system. The robustness of the proposed algorithm is verified on this system under different operating conditions and applying a three-phase fault. The nonlinear time-domain simulation results and some performance indices show the effectiveness of the proposed controller in damping power system oscillations and this novel optimization algorithm is compared with particle swarm optimization (PSO).

Keywords: Power system stabilizer, C-Catfish PSO, ITAE objective function, Power system control, Multi-machine power system

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Authors: Yeonjeong Lee, Kyoung-jae Kim, Youngtae Kim

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This study proposes a novel recommender system that uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user’s preference. The proposed model consists of two steps. In the first step, this study uses logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. Then, this study combines the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. In the second step, this study uses the market basket analysis to extract association rules for co-purchased products. Finally, the system selects customers who have high likelihood to purchase products in each product group and recommends proper products from same or different product groups to them through above two steps. We test the usability of the proposed system by using prototype and real-world transaction and profile data. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The results also show that the proposed system may be useful in real-world online shopping store.

Keywords: Product recommender system, Ensemble technique, Association rules, Decision tree, Artificial neural networks.

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Authors: Vladimír Modrák

Abstract:

This paper offers a case study, in which methodological aspects of cell design for transformation the production process are applied. The cell redesign in this work is tightly focused to reach optimization of material flows under real manufacturing conditions. Accordingly, more individual techniques were aggregated into compact methodical procedure with aim to built one-piece flow production. Case study was concentrated on relatively typical situation of transformation from batch production to cellular manufacturing.

Keywords: Product/Quantity analysis, layout, design, manufacturing process.

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Authors: Abdulbaset Saad, Adel Younis, Zuomin Dong

Abstract:

For design optimization with high-dimensional expensive problems, an effective and efficient optimization methodology is desired. This work proposes a series of modification to the Differential Evolution (DE) algorithm for solving computation Intensive Black-Box Problems. The proposed methodology is called Radial Basis Meta-Model Algorithm Assisted Differential Evolutionary (RBF-DE), which is a global optimization algorithm based on the meta-modeling techniques. A meta-modeling assisted DE is proposed to solve computationally expensive optimization problems. The Radial Basis Function (RBF) model is used as a surrogate model to approximate the expensive objective function, while DE employs a mechanism to dynamically select the best performing combination of parameters such as differential rate, cross over probability, and population size. The proposed algorithm is tested on benchmark functions and real life practical applications and problems. The test results demonstrate that the proposed algorithm is promising and performs well compared to other optimization algorithms. The proposed algorithm is capable of converging to acceptable and good solutions in terms of accuracy, number of evaluations, and time needed to converge.

Keywords: Differential evolution, engineering design, expensive computations, meta-modeling, radial basis function, optimization.

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Authors: S. Venkateswaran, C. Mallika Parveen

Abstract:

The fluid flow and the properties of the hydraulic fluid inside a torque converter are the main topics of interest in this research. The primary goal is to investigate the applicability of various viscous fluids inside the torque converter. The Taguchi optimization method is adopted to analyse the fluid flow in a torque converter from a design perspective. Calculations are conducted in maximizing the pressure since greater the pressure, greater the torque developed. Using the values of the S/N ratios obtained, graphs are plotted. Computational Fluid Dynamics (CFD) analysis is also conducted.

Keywords: Hydraulic fluid, Taguchi's method, optimization, pressure, torque.

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Authors: Ching-I Chen

Abstract:

The continued rise of e-commerce is the main driver of the rapid growth of global online purchase. Consumers can nearly buy everything they want at one occasion through online shopping. The purchase behavior models which focus on single product category are insufficient to describe online shopping behavior. Therefore, analysis of multi-category purchase gets more and more popular. For example, market basket analysis explores customers’ buying tendency of the association between product categories. The information derived from market basket analysis facilitates to make cross-selling strategies and product recommendation system.

To detect the association between different product categories, we use the market basket analysis with the multidimensional scaling technique to build an associated map which describes how likely multiple product categories are bought at the same time. Besides, we also build an inter-purchase time model for associated products to describe how likely a product will be bought after its associated product is bought. We classify inter-purchase time behaviors of multi-category products into nine types, and use a mixture regression model to integrate those behaviors under our assumptions of purchase sequences. Our sample data is from comScore which provides a panelist-label database that captures detailed browsing and buying behavior of internet users across the United States. Finding the inter-purchase time from books to movie is shorter than the inter-purchase time from movies to books. According to the model analysis and empirical results, this research finally proposes the applications and recommendations in the management.

Keywords: Multiple-category purchase behavior, inter-purchase time, market basket analysis.

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Authors: R. Hashemi, M.H.Kargarnovin

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This paper presents the identification of the impact force acting on a simply supported beam. The force identification is an inverse problem in which the measured response of the structure is used to determine the applied force. The identification problem is formulated as an optimization problem and the genetic algorithm is utilized to solve the optimization problem. The objective function is calculated on the difference between analytical and measured responses and the decision variables are the location and magnitude of the applied force. The results from simulation show the effectiveness of the approach and its robustness vs. the measurement noise and sensor location.

Keywords: Genetic Algorithm, Inverse problem, Optimization, Vibration.

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Authors: Hossein Nourkhiz Mahjoub, Mohsen Shiva

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Wireless Mesh Networking is a promising proposal for broadband data transmission in a large area with low cost and acceptable QoS. These features- trade offs in WMNs is a hot research field nowadays. In this paper a mathematical optimization framework has been developed to maximize throughput according to upper bound delay constraints. IEEE 802.11 based infrastructure backhauling mode of WMNs has been considered to formulate the MINLP optimization problem. Proposed method gives the full routing and scheduling procedure in WMN in order to obtain mentioned goals.

Keywords: Mixed-Integer Non Linear Programming (MINLP), routing and scheduling, throughput, wireless mesh networks (WMNs)

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Authors: Chen-Chien Hsu, Guo-Tang Dai

Abstract:

This paper presents a particle swarm optimization (PSO) based approach for multiple object tracking based on histogram matching. To start with, gray-level histograms are calculated to establish a feature model for each of the target object. The difference between the gray-level histogram corresponding to each particle in the search space and the target object is used as the fitness value. Multiple swarms are created depending on the number of the target objects under tracking. Because of the efficiency and simplicity of the PSO algorithm for global optimization, target objects can be tracked as iterations continue. Experimental results confirm that the proposed PSO algorithm can rapidly converge, allowing real-time tracking of each target object. When the objects being tracked move outside the tracking range, global search capability of the PSO resumes to re-trace the target objects.

Keywords: multiple object tracking, particle swarm optimization, gray-level histogram, image

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Authors: May-Ling Tan, Yi Su, Chi-Wan Lim, Liang Zhong, Ru-San Tan

Abstract:

This paper describes an automatic algorithm to restore the shape of three-dimensional (3D) left ventricle (LV) models created from magnetic resonance imaging (MRI) data using a geometry-driven optimization approach. Our basic premise is to restore the LV shape such that the LV epicardial surface is smooth after the restoration. A geometrical measure known as the Minimum Principle Curvature (κ2) is used to assess the smoothness of the LV. This measure is used to construct the objective function of a two-step optimization process. The objective of the optimization is to achieve a smooth epicardial shape by iterative in-plane translation of the MRI slices. Quantitatively, this yields a minimum sum in terms of the magnitude of κ 2, when κ2 is negative. A limited memory quasi-Newton algorithm, L-BFGS-B, is used to solve the optimization problem. We tested our algorithm on an in vitro theoretical LV model and 10 in vivo patient-specific models which contain significant motion artifacts. The results show that our method is able to automatically restore the shape of LV models back to smoothness without altering the general shape of the model. The magnitudes of in-plane translations are also consistent with existing registration techniques and experimental findings.

Keywords: Magnetic Resonance Imaging, Left Ventricle, ShapeRestoration, Principle Curvature, Optimization

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Authors: Abhijit Mitra, Harpreet Singh Dhillon

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We present a novel scheme to evaluate sinusoidal functions with low complexity and high precision using cubic spline interpolation. To this end, two different approaches are proposed to find the interpolating polynomial of sin(x) within the range [- π , π]. The first one deals with only a single data point while the other with two to keep the realization cost as low as possible. An approximation error optimization technique for cubic spline interpolation is introduced next and is shown to increase the interpolator accuracy without increasing complexity of the associated hardware. The architectures for the proposed approaches are also developed, which exhibit flexibility of implementation with low power requirement.

Keywords: Arithmetic, spline interpolator, hardware design, erroranalysis, optimization methods.

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Authors: Khairul Jauhari, Achmad Widodo, Ismoyo Haryanto

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In this article, the radial displacement error correction capability of a high precision spindle grinding caused by unbalance force was investigated. The spindle shaft is considered as a flexible rotor mounted on two sets of angular contact ball bearing. Finite element methods (FEM) have been adopted for obtaining the equation of motion of the spindle. In this paper, firstly, natural frequencies, critical frequencies, and amplitude of the unbalance response caused by residual unbalance are determined in order to investigate the spindle behaviors. Furthermore, an optimization design algorithm is employed to minimize radial displacement of the spindle which considers dimension of the spindle shaft, the dynamic characteristics of the bearings, critical frequencies and amplitude of the unbalance response, and computes optimum spindle diameters and stiffness and damping of the bearings. Numerical simulation results show that by optimizing the spindle diameters, and stiffness and damping in the bearings, radial displacement of the spindle can be reduced. A spindle about 4 μm radial displacement error can be compensated with 2 μm accuracy. This certainly can improve the accuracy of the product of machining.

Keywords: Error correction, High precision grinding, Optimization, Radial displacement, Spindle.

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Authors: Rohit Gupta, Ruchika

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In this paper, a PSO based fractional order PID (FOPID) controller is proposed for concentration control of an isothermal Continuous Stirred Tank Reactor (CSTR) problem. CSTR is used to carry out chemical reactions in industries, which possesses complex nonlinear dynamic characteristics. Particle Swarm Optimization algorithm technique, which is an evolutionary optimization technique based on the movement and intelligence of swarm is proposed for tuning of the controller for this system. Comparisons of proposed controller with conventional and fuzzy based controller illustrate the superiority of proposed PSO-FOPID controller.

Keywords: CSTR, Fractional Order PID Controller, Partical Swarm Optimization.

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Authors: Naohiko Honma, Kojiro Suzuki

Abstract:

This paper proposes the concept of aerocapture with aerodynamic-environment-adaptive variable geometry flexible aeroshell that vehicle deploys. The flexible membrane is composed of thin-layer film or textile as its aeroshell in order to solve some problems obstructing realization of aerocapture technique. Multi-objective optimization study is conducted to investigate solutions and derive design guidelines. As a result, solutions which can avoid aerodynamic heating and enlarge the corridor width up to 10% are obtained successfully, so that the effectiveness of this concept can be demonstrated. The deformation-use optimum solution changes its drag coefficient from 1.6 to 1.1, along with the change in dynamic pressure. Moreover, optimization results show that deformation-use solution requires the membrane for which upper temperature limit and strain limit are more than 700 K and 120%, respectively, and elasticity (Young-s modulus) is of order of 106 Pa.

Keywords: Aerocapture, flexible aeroshell, optimization, response surface methodology.

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Authors: Huaizhong Li, C.Peng Lam

Abstract:

State-based testing is frequently used in software testing. Test data generation is one of the key issues in software testing. A properly generated test suite may not only locate the errors in a software system, but also help in reducing the high cost associated with software testing. It is often desired that test data in the form of test sequences within a test suite can be automatically generated to achieve required test coverage. This paper proposes an Ant Colony Optimization approach to test data generation for the state-based software testing.

Keywords: Software testing, ant colony optimization, UML.

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Authors: Varun Singh, Mainak Bandyopadhyay, Maharana Pratap Singh

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The shortest path (SP) problem concerns with finding the shortest path from a specific origin to a specified destination in a given network while minimizing the total cost associated with the path. This problem has widespread applications. Important applications of the SP problem include vehicle routing in transportation systems particularly in the field of in-vehicle Route Guidance System (RGS) and traffic assignment problem (in transportation planning). Well known applications of evolutionary methods like Genetic Algorithms (GA), Ant Colony Optimization, Particle Swarm Optimization (PSO) have come up to solve complex optimization problems to overcome the shortcomings of existing shortest path analysis methods. It has been reported by various researchers that PSO performs better than other evolutionary optimization algorithms in terms of success rate and solution quality. Further Geographic Information Systems (GIS) have emerged as key information systems for geospatial data analysis and visualization. This research paper is focused towards the application of PSO for solving the shortest path problem between multiple points of interest (POI) based on spatial data of Allahabad City and traffic speed data collected using GPS. Geovisualization of results of analysis is carried out in GIS.

Keywords: GIS, Outliers, PSO, Traffic Data.

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Authors: Kyoungwoo Park, Ji-Won Han, Hyo-Jae Lim, Byeong-Sam Kim, Juhee Lee

Abstract:

Shape optimization of the airfoil with high aspect ratio of long endurance unmanned aerial vehicle (UAV) is performed by the multi-objective optimization technology coupled with computational fluid dynamics (CFD). For predicting the aerodynamic characteristics around the airfoil the high-fidelity Navier-Stokes solver is employed and SMOGA (Simple Multi-Objective Genetic Algorithm), which is developed by authors, is used for solving the multi-objective optimization problem. To obtain the optimal solutions of the design variable (i.e., sectional airfoil profile, wing taper ratio and sweep) for high performance of UAVs, both the lift and lift-to-drag ratio are maximized whereas the pitching moment should be minimized, simultaneously. It is found that the lift force and lift-to-drag ratio are linearly dependent and a unique and dominant solution are existed. However, a trade-off phenomenon is observed between the lift-to-drag ratio and pitching moment. As the result of optimization, sixty-five (65) non-dominated Pareto individuals at the cutting edge of design spaces that is decided by airfoil shapes can be obtained.

Keywords: Unmanned aerial vehicle (UAV), Airfoil, CFD, Shape optimization, Lift-to-drag ratio.

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Authors: Whee Yen Wong, Chan Wai Lee, Kim Yeow Tshai

Abstract:

Producing IT products/services required carefully designed. IT development process is intangible and labour intensive. Making optimal use of available resources, both soft (knowledge, skill-set etc.) and hard (computer system, ancillary equipment etc.), is vital if IT development is to achieve sensible economical advantages. Apart from the norm of Project Life Cycle and System Development Life Cycle (SDLC), there is an urgent need to establish a general yet widely acceptable guideline on the most effective and efficient way to precede an IT project in the broader view of Product Life Cycle. The current paper proposes such a framework with two major areas of concern: (1) an integration of IT Products and IT Services within an existing IT Process architecture and; (2) how IT Product and IT Services are built into the framework of Product Life Cycle, Project Life Cycle and SDLC.

Keywords: Mapping of Quality Relationship, IT Processes/IT Products/IT Services, Product Life Cycle, System Development Life Cycle.

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Authors: A. B. Dariane, A. M. Moradi

Abstract:

A direct search approach to determine optimal reservoir operating is proposed with ant colony optimization for continuous domains (ACOR). The model is applied to a system of single reservoir to determine the optimum releases during 42 years of monthly steps. A disadvantage of ant colony based methods and the ACOR in particular, refers to great amount of computer run time consumption. In this study a highly effective procedure for decreasing run time has been developed. The results are compared to those of a GA based model.

Keywords: Ant colony optimization, continuous, metaheuristics, reservoir, decreasing run time, genetic algorithm.

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Authors: Zeshan Ahmad, Matteo Zoppi, Rezia Molfino

Abstract:

The geometric errors in the manufacturing process can be reduced by optimal positioning of the fixture elements in the fixture to make the workpiece stiff. We propose a new fixture layout optimization method N-3-2-1 for large metal sheets in this paper that combines the genetic algorithm and finite element analysis. The objective function in this method is to minimize the sum of the nodal deflection normal to the surface of the workpiece. Two different kinds of case studies are presented, and optimal position of the fixturing element is obtained for different cases.

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

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Authors: Susmi Routray, A. M. Sherry, B. V. R. Reddy

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Asynchronous Transfer Mode (ATM) is widely used in telecommunications systems to send data, video and voice at a very high speed. In ATM network optimizing the bandwidth through dynamic routing is an important consideration. Previous research work shows that traditional optimization heuristics result in suboptimal solution. In this paper we have explored non-traditional optimization technique. We propose comparison of two such algorithms - Genetic Algorithm (GA) and Tabu search (TS), based on non-traditional Optimization approach, for solving the dynamic routing problem in ATM networks which in return will optimize the bandwidth. The optimized bandwidth could mean that some attractive business applications would become feasible such as high speed LAN interconnection, teleconferencing etc. We have also performed a comparative study of the selection mechanisms in GA and listed the best selection mechanism and a new initialization technique which improves the efficiency of the GA.

Keywords: Asynchronous Transfer Mode(ATM), GeneticAlgorithm(GA), Tabu Search(TS).

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Authors: YuriyTasinkevych, Ihor Trots, AndrzejNowicki, Marcin Lewandowski

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The paper presents the optimization problem for the multi-element synthetic transmit aperture method (MSTA) in ultrasound imaging applications. The optimal choice of the transmit aperture size is performed as a trade-off between the lateral resolution, penetration depth and the frame rate. Results of the analysis obtained by a developed optimization algorithm are presented. Maximum penetration depth and the best lateral resolution at given depths are chosen as the optimization criteria. The optimization algorithm was tested using synthetic aperture data of point reflectors simulated by Filed II program for Matlab® for the case of 5MHz 128-element linear transducer array with 0.48 mm pitch are presented. The visualization of experimentally obtained synthetic aperture data of a tissue mimicking phantom and in vitro measurements of the beef liver are also shown. The data were obtained using the SonixTOUCH Research systemequipped with a linear 4MHz 128 element transducerwith 0.3 mm element pitch, 0.28 mm element width and 70% fractional bandwidth was excited by one sine cycle pulse burst of transducer's center frequency.

Keywords: synthetic aperture method, ultrasound imaging, beamforming.

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Authors: Suman Kumar Saha, Rajib Kar, Durbadal Mandal, S. P. Ghoshal

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This paper demonstrates the application of craziness based particle swarm optimization (CRPSO) technique for designing the 8th order low pass Infinite Impulse Response (IIR) filter. CRPSO, the much improved version of PSO, is a population based global heuristic search algorithm which finds near optimal solution in terms of a set of filter coefficients. Effectiveness of this algorithm is justified with a comparative study of some well established algorithms, namely, real coded genetic algorithm (RGA) and particle swarm optimization (PSO). Simulation results affirm that the proposed algorithm CRPSO, outperforms over its counterparts not only in terms of quality output i.e. sharpness at cut-off, pass band ripple, stop band ripple, and stop band attenuation but also in convergence speed with assured stability.

Keywords: IIR Filter, RGA, PSO, CRPSO, Evolutionary Optimization Techniques, Low Pass (LP) Filter, Magnitude Response, Pole-Zero Plot, Stability.

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Authors: C. Rajan, K. Geetha, C. Rasi Priya, R. Sasikala

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Nature is a great source of inspiration for solving complex problems in networks. It helps to find the optimal solution. Metaheuristic algorithm is one of the nature-inspired algorithm which helps in solving routing problem in networks. The dynamic features, changing of topology frequently and limited bandwidth make the routing, challenging in MANET. Implementation of appropriate routing algorithms leads to the efficient transmission of data in mobile ad hoc networks. The algorithms that are inspired by the principles of naturally-distributed/collective behavior of social colonies have shown excellence in dealing with complex optimization problems. Thus some of the bio-inspired metaheuristic algorithms help to increase the efficiency of routing in ad hoc networks. This survey work presents the overview of bio-inspired metaheuristic algorithms which support the efficiency of routing in mobile ad hoc networks.

Keywords: Ant colony optimization algorithm, Genetic algorithm, naturally inspired algorithms and particle swarm optimization algorithm.

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Authors: Angelica I. Aviles, Pilar Sobrevilla, Alicia Casals

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Compensating physiological motion in the context of minimally invasive cardiac surgery has become an attractive issue since it outperforms traditional cardiac procedures offering remarkable benefits. Owing to space restrictions, computer vision techniques have proven to be the most practical and suitable solution. However, the lack of robustness and efficiency of existing methods make physiological motion compensation an open and challenging problem. This work focusses on increasing robustness and efficiency via exploration of the classes of 1−and 2−regularized optimization, emphasizing the use of explicit regularization. Both approaches are based on natural features of the heart using intensity information. Results pointed out the 1−regularized optimization class as the best since it offered the shortest computational cost, the smallest average error and it proved to work even under complex deformations.

Keywords: Motion Compensation, Optimization, Regularization, Beating Heart Surgery, Ill-posed problem.

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