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An algorithm for solving bond pricing problem
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Genetic Algorithm Analysis using the Graph Coloring Method for Solving the University Timetable Problem
Published 2018“…Genetic algorithms were successfully useful to solve many optimization problems including the university Timetable Problem. …”
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An evolutionary algorithm for solving the geometrically constrained site layout problem
Published 2017“…This paper presents an investigation of applying an evolutionary approach to optimally solve the aforementioned layout problem. The proposed algorithm is two-phases: an initialization phase that generates an initial population of layouts through a sequence of mutation operations, and a reproduction phase that evolve the layouts generated in phase one through a sequence of genetic operations aiming at finding an optimal layout. …”
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Efficient convex-elastic net algorithm to solve the Euclideantraveling salesman problem
Published 1998“…This paper describes a hybrid algorithm that combines an adaptive-type neural network algorithm and a nondeterministic iterative algorithm to solve the Euclidean traveling salesman problem (E-TSP). …”
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Modified clarke wright algorithms for solving the realistic vehicle routing problem
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Improved scatter search algorithm for predicting all-atoms protein structures using charmm22 energy model. (c2010)
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Genetic Algorithm for Solving Site Layout Problem with Unequal-Size and Constrained Facilities
Published 2002“…This paper presents an investigation of the applicability of a genetic approach for solving the construction site layout problem. This problem involves coordinating the use of limited site space to accommodate temporary facilities so that transportation cost of materials is minimized. …”
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Scatter search for protein structure prediction. (c2008)
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10
Sample intelligence-based progressive hedging algorithms for the stochastic capacitated reliable facility location problem
Published 2024“…In this paper, we developed two novel algorithms integrating SAA and PHA for solving the CRFLP under uncertainty. …”
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Extreme Early Image Recognition Using Event-Based Vision
Published 2023“…Unlike frame-based imagers, event-based imagers output asynchronous pixel events without the need for global exposure time, therefore lowering both power consumption and latency. …”
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High-Accurate Parameter Identification of PEMFC Using Advanced Multi-Trial Vector-Based Sine Cosine Meta-Heuristic Algorithm
Published 2025“…<p dir="ltr">Development and modeling of proton exchange membrane fuel cells (PEMFCs) need accurate identification of unknown factors affecting mathematical models. …”
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Generic metadata representation framework for social-based event detection, description, and linkage
Published 2020“…The latter are required as the building blocks for event-based Collective Knowledge (CK) organization, where CK underlines the combination of all known data, information, and metadata concerning a given concept or event. …”
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Metaheuristic Algorithm for State-Based Software Testing
Published 2018“…SA evolves a solution by minimizing an energy function that is based on testing objectives such as coverage, diversity, and continuity of events. …”
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Using genetic algorithms to optimize software quality estimation models
Published 2004“…Most such models are constructed using statistical or machine learning techniques. …”
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Capturing outline of fonts using genetic algorithm and splines
Published 2001“…We present a method to convert the original problem into a discrete combinatorial optimization problem and solve it by a genetic algorithm. We also incorporate a corner detection algorithm to detect significant points which are necessary to capture a pleasant looking spline fitting for shapes such as fonts. …”
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Detection of statistically significant network changes in complex biological networks
Published 2017“…</p><h3>Methods</h3><p dir="ltr">In this paper, we propose an improvement over the state-of-the-art based on the Generalized Hamming Distance adopted for evaluating the topological difference between two networks and estimating its statistical significance. The proposed procedure exploits a more effective model selection criteria to generate <i>p</i>-values for statistical significance and is more efficient in terms of computational time and prediction accuracy than literature methods. …”