What is he best known for?
The fields of study he is best known for:
- Mathematical optimization
- Artificial intelligence
- Algorithm
His main research concerns Job shop scheduling, Mathematical optimization, Flow shop scheduling, Simulated annealing and Algorithm.
His studies in Job shop scheduling integrate themes in fields like Preventive maintenance, Dynamic priority scheduling, Operations research and Fair-share scheduling.
The Mathematical optimization study which covers Tardiness that intersects with Optimization problem.
Mostafa Zandieh combines topics linked to Rate-monotonic scheduling with his work on Flow shop scheduling.
His study looks at the relationship between Simulated annealing and topics such as Taguchi methods, which overlap with Completion time.
As part of one scientific family, Mostafa Zandieh deals mainly with the area of Multi-objective optimization, narrowing it down to issues related to the Pareto principle, and often Genetic algorithm.
His most cited work include:
- An immune algorithm approach to hybrid flow shops scheduling with sequence-dependent setup times (208 citations)
- An artificial immune algorithm for the flexible job-shop scheduling problem (182 citations)
- Flexible job-shop scheduling with parallel variable neighborhood search algorithm (171 citations)
What are the main themes of his work throughout his whole career to date?
Mostafa Zandieh mostly deals with Mathematical optimization, Job shop scheduling, Genetic algorithm, Flow shop scheduling and Simulated annealing.
His studies deal with areas such as Algorithm and Tardiness as well as Mathematical optimization.
His biological study spans a wide range of topics, including Preventive maintenance, Rate-monotonic scheduling, Fair-share scheduling and Multi-objective optimization.
The various areas that he examines in his Flow shop scheduling study include Evolutionary algorithm, Artificial neural network and Imperialist competitive algorithm.
His study looks at the intersection of Simulated annealing and topics like Local search with Local optimum and Hybrid algorithm.
His Scheduling research is multidisciplinary, incorporating perspectives in Sequence-dependent setup and Operations research.
He most often published in these fields:
- Mathematical optimization (64.93%)
- Job shop scheduling (41.23%)
- Genetic algorithm (23.22%)
What were the highlights of his more recent work (between 2017-2021)?
- Mathematical optimization (64.93%)
- Operations research (14.69%)
- Genetic algorithm (23.22%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Mathematical optimization, Operations research, Genetic algorithm, Job shop scheduling and Process.
Particularly relevant to Scheduling is his body of work in Mathematical optimization.
His Operations research study combines topics from a wide range of disciplines, such as Metaheuristic and Fuzzy logic.
Mostafa Zandieh has researched Genetic algorithm in several fields, including Simulated annealing, Algorithm, Cluster analysis, Robustness and Perfect competition.
His Job shop scheduling research incorporates elements of Fuzzy number and Pareto principle.
The Process study combines topics in areas such as Production, Work in process, Product and Data science.
Between 2017 and 2021, his most popular works were:
- A hybrid MCDM approach for order distribution in a multiple-supplier supply chain: A case study (15 citations)
- Drawing a Strategy Canvas Using the Fuzzy Best–Worst Method (14 citations)
- An efficient bi-objective algorithm to solve re-entrant hybrid flow shop scheduling with learning effect and setup times (13 citations)
In his most recent research, the most cited papers focused on:
- Mathematical optimization
- Artificial intelligence
- Statistics
Mostafa Zandieh mostly deals with Mathematical optimization, Job shop scheduling, Genetic algorithm, Robustness and Supply chain.
As part of his studies on Mathematical optimization, he often connects relevant areas like Fuzzy logic.
His work in the fields of Job shop scheduling, such as Flow shop scheduling and Tardiness, overlaps with other areas such as Workload.
His Genetic algorithm study combines topics in areas such as Algorithm and Speedup.
His work on Simulated annealing and Premature convergence as part of general Algorithm study is frequently linked to Line, Out-of-kilter algorithm and Water flow, therefore connecting diverse disciplines of science.
His work in the fields of Supply chain network overlaps with other areas such as Sustainable distribution and Distribution networks.
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