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Development of multi-objective optimization methods for integrated scheduling of handling equipment (AGVs, QCs, SP-AS/RS) in automated container terminals
Published 2012“…Therefore, two meta-heuristic algorithms, namely genetic algorithm (GA) and simulated annealing (SA) algorithm, were developed to optimize the integrated scheduling of handling equipment. …”
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Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms
Published 2020“…The IEM algorithm uses the attraction-repulsion mechanism to change the positions of solutions towards the optimality. …”
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Hybrid conjugate gradient methods using strong Wolfe line search for Whale Optimization Algorithm / Wan Nur Athirah Wan Mohd Zakirudin
Published 2023“…The nonlinear conjugate gradient (CG) method recently is the most used iterative methods for solving optimizing problems because it requires less storage and easy for implementation. …”
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Robotic indoor path planning using dijkstra's algorithm with multi-layer dictionaries
Published 2016“…The adjacency matrix is the naive storage structure of the algorithm. This storage structure has limited the use of the algorithm as it expands large storage space. …”
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Modelling of optimal placement and sizing of battery energy storage system using hybrid whale optimization algorithm and artificial immune system for total system losses reduct...
Published 2023“…Besides, an optimization algorithm with high efficiency is important to ensure the attainment of optimal solutions, where the optimization algorithms like genetic algorithm and particle swarm optimization are known to have high possibility of being trapped in local optimal points. …”
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New Quasi-Newton Equation And Method Via Higher Order Tensor Models
Published 2010“…By using a new equation, the BFGS method is modified. …”
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Quasi-Newton methods based on ordinary differential equation approach for unconstrained nonlinear optimization
Published 2014“…Under suitable assumptions, global convergence of the proposed method is proved. Practical insights on the effectiveness of these approaches on a set of test functions are given by a numerical comparison with that of the limited memory BFGS algorithm (L-BFGS) and conjugate gradient algorithm (CG).…”
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Globalization of Barzilai and Borwein Method for Unconstrained Optimization
Published 2009“…A review of the minimization methods currently available that can be used to solve unconstrained optimization is also given. …”
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Energy management system for optimal operation of microgrid consisting of PV, fuel cell and battery / Shivashankar Sukumar
Published 2017“…The BESS sizing problem is solved using grey wolf optimizer (GWO), particle swarm optimization (PSO), artificial bee colony (ABC), gravitational search algorithm (GSA), and genetic algorithm (GA). …”
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12
Evaluation of Search Result of Document Search Based GA (DSEGA)
Published 2004“…Although i has become easier to collect and store information in document collections, it has become increasingly difficult to retrieve relevant information from these large document collections. Genetic algorithms describe a set of optimization techniques that given a goal or fitness function are used to search a space for optimal points. …”
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Quasi-Newton type method via weak secant equations for unconstrained optimization
Published 2021“…The convergence analysis is presented for these memoryless methods under some standard assumptions. Numerical experiments are carried out using standard test problems and show that the proposed methods are superior to some existing conjugate gradient methods, in terms of iterations and function evaluations required to reach the optimal solutions. …”
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14
Development of an integrated scheduling model for handling equipment in automated port container terminals
Published 2014“…As the integrated scheduling of handling equipment is a “non-deterministic polynomialtime hard” (NP-hard) problem and also the computation time and ease of application are so important for real practices of the scheduling methods, So a meta-heuristic algorithm based on Genetic Algorithm is developed, in which, new operators create solutions considering the constraints of the problem and also a heuristic rule proposed which assigns the ALVs to the tasks. …”
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15
Multiple and solid data background scheme for testing static single cell faults on SRAM memories
Published 2013“…Therefore, the purpose of this thesis is to introduce a Data Background (DB) scheme to generate an optimal March Test Algorithm (MTA) for detecting faults of memory that are undetectable using existing algorithms. …”
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16
Power System State Estimation In Large-Scale Networks
Published 2010“…Its optimal performance is required in order to operate the power system in a safe, secure and economic manner. …”
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Logistics center location-inventory-routing problem optimization: a systematic review using PRISMA method
Published 2022“…When dealing with the LIRP, heuristic and metaheuristic algorithms are the most widely used solution methodologies in the literature. …”
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Sizing and placement of battery-coupled distributed photovoltaic generations
Published 2017“…To estimate the output from PV modules, 15-year solar irradiance data is modeled using the beta probability density function. Mixed-integer optimization using a genetic algorithm is employed for solving the optimization problem. …”
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Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications
Published 2023“…Carbon; Decarbonization; Electric energy storage; Fossil fuels; Global warming; Renewable energy resources; Carbon emissions; Decarbonisation; Energy storage system; Method; Microgrid; Optimal energy; Optimization algorithms; Sizing; Storage systems; System sizings; Cost effectiveness…”
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Optimal allocation of battery energy storage system using whale optimization algorithm
Published 2023“…Battery storage; Electric batteries; Battery energy storage systems; Firefly algorithms; Loss reduction; Meta-heuristic methods; Optimal allocation; Optimization algorithms; Overall system loss reduction; Performance; System loss; Whale optimization algorithm; Particle swarm optimization (PSO)…”
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