102 research outputs found

    SOLUTION AND PERFORMANCE EVALUATION OF TRANS-SHIPMENT PROBLEM USING A MINIMUM SPANNING TREE APPROACH

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    Purpose: Transportation problem plays an important role in operations research. The more generalized cases of transportation problems are trans-shipment problems. Further, the trans-shipment problems may have a set of trans-shipment nodes, or the source/destination nodes themselves act as the trans-shipment nodes. The study of the trans-shipment problems and their solution methodology is the goal of this paper. Methodology: The solution of a trans-shipment problem could be done by transferring it to a transportation problem. Further, there exist various conventional methods for solving the transportation problem. The present paper discusses about the scope of application of an existing heuristic algorithm directly over the trans-shipment problem. The heuristic is based on the minimum spanning tree approach. We implement the algorithm over a test problem and further compare its performance by the performance of the corresponding algorithm Vogel’s Approximation Method. Main findings: The spanning tree approach gives a better solution or almost the nearby solution as compared to the solution obtained by Vogel’s Approximation Method. Implications: The solution obtained by the spanning-tree approach takes lesser computational effort to reach a better feasible solution. The novelty of study: The algorithm to deal with the trans-shipment problem i.e. for finding the feasible solution of the trans-shipment problem is the main focus of this paper.Transportation Proble

    A Literature Review of Cuckoo Search Algorithm

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    Optimization techniques play key role in real world problems. In many situations where decisions are taken based on random search they are used. But choosing optimal Optimization algorithm is a major challenge to the user. This paper presents a review on Cuckoo Search Algorithm which can replace many traditionally used techniques. Cuckoo search uses Levi flight strategy based on Egg laying Radius in deriving the solution specific to problem. CS optimization algorithm increases the efficiency, accuracy, and convergence rate. Different categories of the cuckoo search and several applications of the cuckoo search are reviewed. Keywords: Cuckoo Search Optimization, Applications , Levy Flight DOI: 10.7176/JEP/11-8-01 Publication date:March 31st 202

    The Project Scheduling Problem with Non-Deterministic Activities Duration: A Literature Review

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    Purpose: The goal of this article is to provide an extensive literature review of the models and solution procedures proposed by many researchers interested on the Project Scheduling Problem with nondeterministic activities duration. Design/methodology/approach: This paper presents an exhaustive literature review, identifying the existing models where the activities duration were taken as uncertain or random parameters. In order to get published articles since 1996, was employed the Scopus database. The articles were selected on the basis of reviews of abstracts, methodologies, and conclusions. The results were classified according to following characteristics: year of publication, mathematical representation of the activities duration, solution techniques applied, and type of problem solved. Findings: Genetic Algorithms (GA) was pointed out as the main solution technique employed by researchers, and the Resource-Constrained Project Scheduling Problem (RCPSP) as the most studied type of problem. On the other hand, the application of new solution techniques, and the possibility of incorporating traditional methods into new PSP variants was presented as research trends. Originality/value: This literature review contents not only a descriptive analysis of the published articles but also a statistical information section in order to examine the state of the research activity carried out in relation to the Project Scheduling Problem with non-deterministic activities duration.Peer Reviewe

    System reliability using generalized intuitionistic fuzzy Rayleigh lifetime distribution

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    Reliability analysis as one of the important research topics in engineering has been researched by a number of authors. Reliability in classical distributions is based on precise parameters. It is usually assumed that parameters of distributions are precise real numbers. However, in the real world, the data sometimes cannot be measured and recorded precisely. In this paper, the concept of fuzzy reliability is extended by the idea of generalized intuitionistic fuzzy reliability. We investigate the reliability characteristics of systems using Rayleigh lifetime distribution, in which the lifetime parameter is assumed to be generalized intuitionistic fuzzy number. Generalized intuitionistic fuzzy reliability, generalized intuitionistic fuzzy hazard function, generalized intuitionistic fuzzy mean time to failure and their cut sets are discussed when the systems follow generalized intuitionistic fuzzy Rayleigh lifetime distribution. In this approach, for every special cut set, reliability curve and hazard curve are like a band with upper and lower bound. A numerical example is given to illustrate the proposed approach. Further, reliability analysis of the series and parallel systems are done

    CLOUD COMPUTING BASED INFRASTRUCTURE IN EDUCATION: INVESTING INTO THE PRIVATE INFRASTRUCTURE OR USING OUTSOURCING SERVICES

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    The main challenge for higher education in the nearest future is the global competitiveness, as the present global market requires the higher schools to present their courses in the international level. Thus, traditional universities must adapt educational infrastructures in response with the global requirement. Outsourcing of cloud computing based services increased over the years. The solutions allow not only create more effective teaching methods and new communication chances for the whole education society, but also to reduce costs of installing and maintaining programs.Aim of the article is to prepare a cost/benefit case analysis between investing into the private information and communication technology infrastructure and using outsourcing services. This paper focuses attention on cloud computing based information and communication technology infrastructures of two higher education institutions.Research methods include analysis of scientific literature, review of legal institutional documentation and reports and interviews with institutional representatives about education practices

    Enhanced dynamic source routing for verifying trust in mobile ad hoc network for secure routing

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    Secure data transfer in mobile ad hoc network (MANET) against malicious attacks is of immense importance. In this paper, we propose a new enhanced trust model for securing the MANET using trust-based scheme that uses both blind trust and referential trust. In order to do this, the trust relationship function has to be integrated with the dynamic source routing (DSR) protocol for making the protocol more secure. We thoroughly analyze the DSR protocol and generate the performance matrices for the data pertaining to packets sent, packets received, packets loss, and throughput. We also analyze the outcome attained from the improvised trust establishment scheme by using the three algorithm implementations in NS2 simulator for detecting and preventing various types of attacks

    Hybrid feature selection method based on particle swarm optimization and adaptive local search method

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    Machine learning has been expansively examined with data classification as the most popularly researched subject. The accurateness of prediction is impacted by the data provided to the classification algorithm. Meanwhile, utilizing a large amount of data may incur costs especially in data collection and preprocessing. Studies on feature selection were mainly to establish techniques that can decrease the number of utilized features (attributes) in classification, also using data that generate accurate prediction is important. Hence, a particle swarm optimization (PSO) algorithm is suggested in the current article for selecting the ideal set of features. PSO algorithm showed to be superior in different domains in exploring the search space and local search algorithms are good in exploiting the search regions. Thus, we propose the hybridized PSO algorithm with an adaptive local search technique which works based on the current PSO search state and used for accepting the candidate solution. Having this combination balances the local intensification as well as the global diversification of the searching process. Hence, the suggested algorithm surpasses the original PSO algorithm and other comparable approaches, in terms of performance

    Selecting Statistical Characteristics of Brain Signals to Detect Epileptic Seizures using Discrete Wavelet Transform and Perceptron Neural Network

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    Electroencephalogram signals (EEG) have always been used in medical diagnosis. Evaluation of the statistical characteristics of EEG signals is actually the foundation of all brain signal processing methods. Since the correct prediction of disease status is of utmost importance, the goal is to use those models that have minimum error and maximum reliability. In anautomatic epileptic seizure detection system, we should be able to distinguish between EEG signals before, during and after seizure. Extracting useful characteristics from EEG data can greatly increase the classification accuracy. In this new approach, we first parse EEG signals to sub-bands in different categories with the help of discrete wavelet transform(DWT) and then we derive statistical characteristics such as maximum, minimum, average and standard deviation for each sub-band. A multilayer perceptron (MLP)neural network was used to assess the different scenarios of healthy and seizure among the collected signal sets. In order to assess the success and effectiveness of the proposed method, the confusion matrix was used and its accuracy was achieved98.33 percent. Due to the limitations and obstacles in analyzing EEG signals, the proposed method can greatly help professionals experimentally and visually in the classification and diagnosis of epileptic seizures
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