R
Reza Tavakkoli-Moghaddam
Researcher at University of Tehran
Publications - 724
Citations - 17195
Reza Tavakkoli-Moghaddam is an academic researcher from University of Tehran. The author has contributed to research in topics: Supply chain & Fuzzy logic. The author has an hindex of 56, co-authored 650 publications receiving 13200 citations. Previous affiliations of Reza Tavakkoli-Moghaddam include University of British Columbia & Education and Research Network.
Papers
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A new multi-objective stochastic model for a forward/reverse logistic network design with responsiveness and quality level
TL;DR: In this article, a stochastic multi-objective model for forward/reverse logistic network design under a uncertain environment including three echelons in forward direction (i.e., suppliers, plants, and distribution centers) and two echelon in backward direction (e.g., collection centers and disposal centers).
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Reliability optimization of series-parallel systems with a choice of redundancy strategies using a genetic algorithm
TL;DR: It is demonstrated in this paper that GA is an efficient method for solving a redundancy allocation problem for the series-parallel system when the redundancy strategy can be chosen for individual subsystems.
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Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty
Mohammad Zhalechian,Reza Tavakkoli-Moghaddam,Reza Tavakkoli-Moghaddam,Behzad Zahiri,Mehrdad Mohammadi +4 more
TL;DR: Considering economic, environmental and social impacts, a new sustainable closed-loop location-routing-inventory model under mixed uncertainty is presented in this paper, where the environmental impacts of CO2 emissions, fuel consumption, wasted energy and the social impacts of created job opportunities and economic development are considered.
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Red deer algorithm (RDA): a new nature-inspired meta-heuristic
Amir Mohammad Fathollahi-Fard,Mostafa Hajiaghaei-Keshteli,Reza Tavakkoli-Moghaddam,Reza Tavakkoli-Moghaddam +3 more
TL;DR: The main inspiration of this meta- heuristic algorithm is to originate from an unusual mating behavior of Scottish red deer in a breading season, and the superiority of the proposed RDA shows in comparison with other well-known and recent meta-heuristics.
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The Social Engineering Optimizer (SEO)
TL;DR: This paper aims to develop a simple, intelligent and new single-solution algorithm that has just four main steps and three simple parameters to tune that shows its superiority in comparison with other well-known and recent meta-heuristics.