His primary scientific interests are in Mathematical optimization, Simulated annealing, Fuzzy logic, Operations research and Genetic algorithm. Reza Tavakkoli-Moghaddam integrates Mathematical optimization with Vehicle routing problem in his study. His Simulated annealing research integrates issues from Cellular manufacturing, Tabu search, Control reconfiguration, Job shop and Simulation.
As a member of one scientific family, Reza Tavakkoli-Moghaddam mostly works in the field of Fuzzy logic, focusing on Total cost and, on occasion, Robust optimization. The study incorporates disciplines such as Supply chain, Supply chain management and Metaheuristic in addition to Operations research. His work in Genetic algorithm covers topics such as Robustness which are related to areas like Active redundancy, Triple modular redundancy and Systems design.
Reza Tavakkoli-Moghaddam focuses on Mathematical optimization, Operations research, Fuzzy logic, Genetic algorithm and Supply chain. His Mathematical optimization research incorporates themes from Job shop scheduling and Tardiness. Operations research and Total cost are frequently intertwined in his study.
Fuzzy logic is a subfield of Artificial intelligence that Reza Tavakkoli-Moghaddam tackles. Reza Tavakkoli-Moghaddam interconnects Sorting, Algorithm, Pareto principle and Evolutionary algorithm in the investigation of issues within Genetic algorithm. In his research on the topic of Simulated annealing, Control reconfiguration and Production planning is strongly related with Cellular manufacturing.
The scientist’s investigation covers issues in Operations research, Mathematical optimization, Supply chain, Fuzzy logic and Genetic algorithm. His research on Operations research also deals with topics like
Many of his research projects under Supply chain are closely connected to Vehicle routing problem with Vehicle routing problem, tying the diverse disciplines of science together. His Fuzzy logic study incorporates themes from Reliability engineering and Product. His Genetic algorithm research is multidisciplinary, incorporating elements of Sorting, Algorithm, Particle swarm optimization, Tabu search and Pareto principle.
His scientific interests lie mostly in Operations research, Mathematical optimization, Linear programming, Supply chain and Fuzzy logic. His Operations research research is multidisciplinary, incorporating perspectives in Variation, Imperialist competitive algorithm and Investment. In general Mathematical optimization study, his work on Scheduling, Solver and Genetic algorithm often relates to the realm of Pipeline transport and Order, thereby connecting several areas of interest.
The concepts of his Linear programming study are interwoven with issues in Robust optimization, Pareto principle and Job shop scheduling. His research in the fields of Supply chain network overlaps with other disciplines such as Distribution. Reza Tavakkoli-Moghaddam combines subjects such as Closed loop, Metaheuristic, Public transport, Price elasticity of demand and Particle swarm optimization with his study of Fuzzy logic.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
A new multi-objective stochastic model for a forward/reverse logistic network design with responsiveness and quality level
Majid Ramezani;Mahdi Bashiri;Reza Tavakkoli-Moghaddam.
Applied Mathematical Modelling (2013)
Reliability optimization of series-parallel systems with a choice of redundancy strategies using a genetic algorithm
Reza Tavakkoli-Moghaddam;Reza Tavakkoli-Moghaddam;Jalal Safari;Farrokh Sassani.
Reliability Engineering & System Safety (2008)
Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty
M. Zhalechian;R. Tavakkoli-Moghaddam;R. Tavakkoli-Moghaddam;B. Zahiri;M. Mohammadi.
Transportation Research Part E-logistics and Transportation Review (2016)
A HYBRID MULTI-OBJECTIVE IMMUNE ALGORITHM FOR A FLOW SHOP SCHEDULING PROBLEM WITH BI-OBJECTIVES: WEIGHTED MEAN COMPLETION TIME AND WEIGHTED MEAN TARDINESS
Reza Tavakkoli-Moghaddam;Alireza Rahimi-Vahed;Ali Hossein Mirzaei.
Information Sciences (2007)
Solving a group layout design model of a dynamic cellular manufacturing system with alternative process routings, lot splitting and flexible reconfiguration by simulated annealing
R. Kia;A. Baboli;N. Javadian;R. Tavakkoli-Moghaddam.
Computers & Operations Research (2012)
Group decision making based on novel fuzzy modified TOPSIS method
Behnam Vahdani;S. Meysam Mousavi;Reza Tavakkoli-Moghaddam.
Applied Mathematical Modelling (2011)
Reliable design of a forward/reverse logistics network under uncertainty: A robust-M/M/c queuing model
Behnam Vahdani;Reza Tavakkoli-Moghaddam;Mohammad Modarres;Armand Baboli.
Transportation Research Part E-logistics and Transportation Review (2012)
A novel two-phase group decision making approach for construction project selection in a fuzzy environment
S. Ebrahimnejad;S.M. Mousavi;R. Tavakkoli-Moghaddam;H. Hashemi.
Applied Mathematical Modelling (2012)
Solving a dynamic cell formation problem using metaheuristics
Reza Tavakkoli-Moghaddam;Mir-Bahador Aryanezhad;Nima Safaei;Amir Azaron.
Applied Mathematics and Computation (2005)
An efficient algorithm for solving a new mathematical model for a quay crane scheduling problem in container ports
R. Tavakkoli-Moghaddam;A. Makui;S. Salahi;M. Bazzazi.
Computers & Industrial Engineering (2009)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: