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Masoud Mahootchi
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2020 – today
- 2024
- [j19]Fatemeh Karamiyan
, Masoud Mahootchi
A personalized ranking method based on inverse reinforcement learning in search engines. Eng. Appl. Artif. Intell. 136: 108915 (2024) - [j18]Mahdi Massahi Kh.
A deep Q-learning based algorithmic trading system for commodity futures markets. Expert Syst. Appl. 237(Part C): 121711 (2024) - [j17]Mohsen Sadeghi-Dastaki
Managing Knowledge Requirements in the NPD Portfolio Selection Process Using Knowledge Clustering and Prioritization: A Case Study of an Australian Train Operator. IEEE Trans. Engineering Management 71: 2973-2985 (2024) - 2023
- [j16]Zeinab Rahimi Rise
Fusing clinical and image data for detecting the severity of breast cancer by a novel hierarchical approach. J. Exp. Theor. Artif. Intell. 35(2): 207-230 (2023) - 2022
- [j15]Mohsen Sadeghi-Dastaki
A two-phase decision-making model for product development based on a product-oriented knowledge inventory model. J. Knowl. Manag. 26(4): 943-971 (2022)
2010 – 2019
- 2019
- [j14]Faraz Salehi, Masoud Mahootchi, Seyed Mohamad Moattar Husseini:
Developing a robust stochastic model for designing a blood supply chain network in a crisis: a possible earthquake in Tehran. Ann. Oper. Res. 283(1-2): 679-703 (2019) - [j13]Ehsan Hajizadeh
A new NN-PSO hybrid model for forecasting Euro/Dollar exchange rate volatility. Neural Comput. Appl. 31(7): 2063-2071 (2019) - 2018
- [j12]Masoud Mahootchi, Sajjad Golmohammadi:
Developing a new stochastic model considering bi-directional relations in a natural disaster: a possible earthquake in Tehran (the Capital of Islamic Republic of Iran). Ann. Oper. Res. 269(1-2): 439-473 (2018) - [j11]Taher Ahmadi
Optimal randomized ordering policies for a capacitated two-echelon distribution inventory system. Comput. Ind. Eng. 124: 88-99 (2018) - [j10]Ehsan Hajizadeh
Optimized radial basis function neural network for improving approximate dynamic programming in pricing high dimensional options. Neural Comput. Appl. 30(6): 1783-1794 (2018) - 2017
- [j9]Jamal Shahrabi, Mohammad Amin Adibi, Masoud Mahootchi:
A reinforcement learning approach to parameter estimation in dynamic job shop scheduling. Comput. Ind. Eng. 110: 75-82 (2017) - [j8]Amir-Mohsen Karimi-Majd, Masoud Mahootchi, Amir Zakery
A reinforcement learning methodology for a human resource planning problem considering knowledge-based promotion. Simul. Model. Pract. Theory 79: 87-99 (2017) - 2016
- [j7]Mohammad Fattahi
Integrated strategic and tactical supply chain planning with price-sensitive demands. Ann. Oper. Res. 242(2): 423-456 (2016) - 2015
- [j6]Saeed Marzban, Masoud Mahootchi, Alireza Arshadi Khamseh:
Developing a multi-period robust optimization model considering American style options. Ann. Oper. Res. 233(1): 305-320 (2015) - [j5]Amir-Mohsen Karimi-Majd, Masoud Mahootchi:
A new data mining methodology for generating new service ideas. Inf. Syst. E Bus. Manag. 13(3): 421-443 (2015) - [j4]Taha Hossein Hejazi
Optimization of Degree of Conformance in Multiresponse-Multistage Systems with a Simulation-based Metaheuristic. Qual. Reliab. Eng. Int. 31(4): 645-658 (2015) - [j3]Farzad Zeinali, Masoud Mahootchi, Mohammad Mehdi Sepehri:
Resource planning in the emergency departments: A simulation-based metamodeling approach. Simul. Model. Pract. Theory 53: 123-138 (2015) - 2014
- [j2]Mohammad Fattahi
A new approach for maintenance scheduling of generating units in electrical power systems based on their operational hours. Comput. Oper. Res. 50: 61-79 (2014) - [j1]Masoud Mahootchi, Hamid R. Tizhoosh, Kumaraswamy Ponnambalam:
Oppositional extension of reinforcement learning techniques. Inf. Sci. 275: 101-114 (2014)
2000 – 2009
- 2009
- [b1]Masoud Mahootchi:
Storage System Management Using Reinforcement Learning Techniques and Nonlinear Models. University of Waterloo, Ontario, Canada, 2009 - 2008
- [p1]Masoud Mahootchi, Hamid R. Tizhoosh, Kumaraswamy Ponnambalam:
Opposition Mining in Reservoir Management. Oppositional Concepts in Computational Intelligence 2008: 299-321
Coauthor Index
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last updated on 2024-09-10 01:16 CEST by the dblp team
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