A tradeoff model for green supply chain planning: A leanness-versus-greenness analysis B Fahimnia, J Sarkis, A Eshragh Omega 54, 173-190, 2015 | 286 | 2015 |
Tactical supply chain planning under a carbon tax policy scheme: A case study B Fahimnia, J Sarkis, A Choudhary, A Eshragh International Journal of Production Economics 164, 206-215, 2015 | 175 | 2015 |
Demand forecasting in the presence of systematic events: Cases in capturing sales promotions M Abolghasemi, J Hurley, A Eshragh, B Fahimnia International Journal of Production Economics 230, 107892, 2020 | 65 | 2020 |
Planning of complex supply chains: A performance comparison of three meta-heuristic algorithms B Fahimnia, H Davarzani, A Eshragh Computers & Operations Research 89, 241-252, 2018 | 63 | 2018 |
A hybrid simulation-optimization algorithm for the Hamiltonian cycle problem A Eshragh, JA Filar, M Haythorpe Annals of Operations Research 189, 103-125, 2011 | 34 | 2011 |
Modeling the dynamics of the COVID-19 population in Australia: A probabilistic analysis A Eshragh, S Alizamir, P Howley, E Stojanovski PLoS ONE 15 (10), e0240153, 2020 | 33 | 2020 |
Average-reward model-free reinforcement learning: a systematic review and literature mapping V Dewanto, G Dunn, A Eshragh, M Gallagher, F Roosta arXiv preprint arXiv:2010.08920, 2020 | 28 | 2020 |
A projection-adapted cross entropy (PACE) method for transmission network planning A Eshragh, J Filar, A Nazar Energy Systems 2, 189-208, 2011 | 27 | 2011 |
The Importance of Environmental Factors in Forecasting Australian Power Demand A Eshragh, B Ganim, T Perkins, K Bandara Environmental Modeling & Assessment, 2021 | 20 | 2021 |
A new approach to distribution fitting: decision on beliefs A Eshragh, M MODARES JOURNAL OF INDUSTRIAL AND SYSTEMS ENGINEERING (JISE) 3 (1), 56-71, 2009 | 19 | 2009 |
On transition matrices of Markov chains corresponding to Hamiltonian cycles K Avrachenkov, A Eshragh, JA Filar Annals of Operations Research 243 (1), 19-35, 2016 | 17 | 2016 |
Hamiltonian cycles, random walks, and discounted occupational measures A Eshragh, J Filar Mathematics of Operations Research 36 (2), 258-270, 2011 | 17 | 2011 |
LSAR: Efficient Leverage Score Sampling Algorithm for the Analysis of Big Time Series Data A Eshragh, F Roosta, A Nazari, MW Mahoney Journal of Machine Learning Research, 2022 | 14 | 2022 |
A new approach to select the best subset of predictors in linear regression modelling: bi-objective mixed integer linear programming H Charkhgard, A Eshragh The ANZIAM Journal 61 (1), 64-75, 2019 | 10 | 2019 |
Uniform Fractional Part: A simple fast method for generating continuous random variates H MAHLOUJI, JA ESHRAGH, MH ABOUEI, N IZADI SCIENTIA IRANICA 15 (5), 613-622, 2008 | 9 | 2008 |
Hamiltonian cycles and subsets of discounted occupational measures A Eshragh, JA Filar, T Kalinowski, S Mohammadian Mathematics of Operations Research, 2019 | 8 | 2019 |
An analytical bound on the fleet size in vehicle routing problems: a dynamic programming approach A Eshragh, R Esmaeilbeigi, R Middleton Operations Research Letters, 2020 | 6 | 2020 |
Fisher Information for a partially observable simple birth process NG Bean, A Eshragh, JV Ross Communications in Statistics-Theory and Methods 45 (24), 7161-7183, 2016 | 6 | 2016 |
On binomial observations of continuous-time Markovian population models NG Bean, R Elliott, A Eshragh, JV Ross Journal of Applied Probability 52 (2), 457-472, 2015 | 6 | 2015 |
Hamiltonian Cycles and the Space of Discounted Occupational Measures A Eshragh LAP Lambert Academic Publishing, 2011 | 5 | 2011 |