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Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty
Published 2024“…This thesis also aims to solve the low-carbon LIRP model with uncertainty factors such as carbon trading, customer demand, shortages, and soft time windows using advanced algorithms. …”
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Formulating and solving stochastic truck and trailer routing problems using meta-heuristic algorithms / Seyedmehdi Mirmohammadsadeghi
Published 2015“…The solutions have been significantly improved by the algorithms. This issue has been formulated under chance constrained programming (CCP) model and stochastic programming model with recourse (SPR). …”
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Agent-based extraction algorithm for computational problem solving
Published 2015“…Modeling Computational Problem Solving (CPS) is the main issue in teaching programming where the given text is needed to be transformed into a model then later into a programming language. …”
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Bi-objective mixed integer nonlinear programming model for low carbon location-inventory-routing problem with time windows and customer satisfaction
Published 2024“…This paper proposes a bi-objective mixed-integer nonlinear programming model with time window constraints that satisfies the normal distribution of stochastic customer demand. …”
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Simulation and Visualization of TSP Using Ant Colony Optimization
Published 2023“…With Windows as the operating system and the C# programming language in Visual Studio 2019, the program complies with the Extreme Programming (XP) software development method. …”
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Vehicle routing problem: models and solutions
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Comparative Analysis Using Bayesian Approach To Neural Network Of Translational Initiation Sites In Alternative Polymorphic Contex
Published 2012“…The objectives of this paper are to develop useful algorithms and to build a new classification model for the case study.The first approach of neural network includes training on algorithms of Resilient Backpropagation,Scaled Conjugate Gradient Backpropagation and Levenberg-Marquardt.The outputs are used in comparison with Bayesian Neural Network for efficiency comparison.The results showed that Resilient Backpropagation have the consistency in all measurement but performs less in accuracy.In second approach,the Bayesian Classifier_01 outperforms the Resilient Backpropagation by successfully increasing the overall prediction accuracy by 16.0%.The Bayesian Classifier_02 is built to improve the accuracy by adding new features of chemical properties as selected by the Information Gain Ratio method,and increasing the length of the window sequence to 201.The result shows that the built model successfully increases the accuracy by 96.0%.In comparison,the Bayesian model outperforms Tikole and Sankararamakrishnan (2008) by increasing the sensitivity by 10% and specificity by 26%. …”
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The design and implementation of a two and three-dimensional triangular irregular network based GIS
Published 2000“…To facilitate the output of the developed methods and algorithms, software called TinSoft, which is a Windows-based Multiple Document Interface software was developed in this research.…”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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FPGA Implementation of Emergency Door Car Entry System
Published 2008“…VHSIC is an acronym for Very High-Speed Integrated Circuits. VHDL can be used to model a digital system at many levels of abstraction ranging from the algorithmic level to the gate level. …”
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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Development Of Distributed Grid-Based Hydrological Model And Floodplain Inundation Management System
Published 2008“…The simulation algorithms of the rainfall-runoff model have operated on grid bases compatible with the MATLAB programming language, which has been used to write instructions to many grid-based operations. …”
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