His primary scientific interests are in Mathematical optimization, Genetic algorithm, Inventory control, Fuzzy logic and Simulated annealing. His study in the fields of Particle swarm optimization under the domain of Mathematical optimization overlaps with other disciplines such as Vendor. The various areas that Seyed Taghi Akhavan Niaki examines in his Genetic algorithm study include Harmony search, Pareto principle, Inventory cost, Sorting and Constraint.
The study incorporates disciplines such as Budget constraint, Type, Independent and identically distributed random variables and Sensitivity in addition to Inventory control. His work on Fuzzy number and Defuzzification as part of general Fuzzy logic research is frequently linked to Economic order quantity, thereby connecting diverse disciplines of science. His biological study spans a wide range of topics, including Supply chain network, Optimization problem and Time horizon.
Seyed Taghi Akhavan Niaki mainly investigates Mathematical optimization, Genetic algorithm, Control chart, Statistics and Algorithm. His study in Mathematical optimization focuses on Particle swarm optimization in particular. His Genetic algorithm research includes elements of Simulated annealing, Pareto principle, Sorting, Fuzzy logic and Optimization problem.
His Control chart research integrates issues from Estimator, Statistical process control, Chart and Autoregressive model. His Estimator study combines topics in areas such as Point estimation and Monte Carlo method. His Statistics research is multidisciplinary, incorporating perspectives in Quality and Shewhart individuals control chart.
His primary areas of study are Mathematical optimization, Genetic algorithm, Quality, Statistics and Reliability. Seyed Taghi Akhavan Niaki has researched Mathematical optimization in several fields, including Taguchi methods and Total cost. His studies in Genetic algorithm integrate themes in fields like Particle swarm optimization, Sorting, Lagrangian relaxation, Benchmark and Optimization problem.
His research in Quality intersects with topics in Environmental economics and Process management. Seyed Taghi Akhavan Niaki has included themes like Control chart and Statistical process monitoring in his Statistics study. The concepts of his Control chart study are interwoven with issues in Chart and Support vector machine.
Seyed Taghi Akhavan Niaki mainly focuses on Mathematical optimization, Genetic algorithm, Benchmark, Quality and Taguchi methods. His study in Mathematical optimization is interdisciplinary in nature, drawing from both Total cost and Nonlinear programming. His Genetic algorithm research incorporates themes from Sorting, Algorithm, Particle swarm optimization and Artificial intelligence.
His Benchmark research is multidisciplinary, incorporating perspectives in Optimization problem and Crossover. The Quality study combines topics in areas such as Control engineering, Statistic and U-statistic. The various areas that Seyed Taghi Akhavan Niaki examines in his Taguchi methods study include Budget constraint, Service level, Random variable, Location-allocation and Learning effect.
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A genetic algorithm for vendor managed inventory control system of multi-product multi-constraint economic order quantity model
Seyed Hamid Reza Pasandideh;Seyed Taghi Akhavan Niaki;Ali Roozbeh Nia.
Expert Systems With Applications (2011)
Fault Diagnosis in Multivariate Control Charts Using Artificial Neural Networks
Seyed Taghi Akhavan Niaki;Babak Abbasi.
Quality and Reliability Engineering International (2005)
Multi-response simulation optimization using genetic algorithm within desirability function framework
Seyed Hamid Reza Pasandideh;Seyed Taghi Akhavan Niaki.
Applied Mathematics and Computation (2006)
Bi-objective optimization of a multi-product multi-period three-echelon supply chain problem under uncertain environments
Seyed Hamid Reza Pasandideh;Seyed Taghi Akhavan Niaki;Kobra Asadi.
Information Sciences (2015)
A hybrid vendor managed inventory and redundancy allocation optimization problem in supply chain management: An NSGA-II with tuned parameters
Javad Sadeghi;Saeid Sadeghi;Seyed Taghi Akhavan Niaki.
Computers & Operations Research (2014)
A soft-computing Pareto-based meta-heuristic algorithm for a multi-objective multi-server facility location problem
Seyed Habib A. Rahmati;Vahid Hajipour;Seyed Taghi Akhavan Niaki.
soft computing (2013)
Forecasting S&P 500 index using artificial neural networks and design of experiments
Seyed Taghi Akhavan Niaki;Saeid Hoseinzade.
Journal of Industrial Engineering, International (2013)
A bi-objective integrated procurement, production, and distribution problem of a multi-echelon supply chain network design
Keyvan Sarrafha;Seyed Habib A. Rahmati;Seyed Taghi Akhavan Niaki;Arash Zaretalab.
Computers & Operations Research (2015)
Optimizing a hybrid vendor-managed inventory and transportation problem with fuzzy demand
Javad Sadeghi;Saeid Sadeghi;Seyed Taghi Akhavan Niaki.
Information Sciences (2014)
Optimizing multi-item multi-period inventory control system with discounted cash flow and inflation: Two calibrated meta-heuristic algorithms
Seyed Mohsen Mousavi;Vahid Hajipour;Seyed Taghi Akhavan Niaki;Najmeh Alikar.
Applied Mathematical Modelling (2013)
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