What is he best known for?
The fields of study he is best known for:
- Statistics
- Mathematical optimization
- Algorithm
The scientist’s investigation covers issues in Mathematical optimization, Metaheuristic, Ant colony optimization algorithms, Combinatorial optimization and Operations research.
Pareto principle, Stochastic optimization and Simulated annealing are among the areas of Mathematical optimization where Walter J. Gutjahr concentrates his study.
His work deals with themes such as Genetic algorithm, Project portfolio management and Heuristic, which intersect with Metaheuristic.
His Ant colony optimization algorithms research includes elements of Swarm intelligence and Meta-optimization.
His research in Combinatorial optimization tackles topics such as Optimization problem which are related to areas like Tabu search, Differential evolution and Graph.
Walter J. Gutjahr focuses mostly in the field of Operations research, narrowing it down to matters related to Greedy algorithm and, in some cases, Weighted arithmetic mean.
His most cited work include:
- A survey on metaheuristics for stochastic combinatorial optimization (391 citations)
- Pareto Ant Colony Optimization: A metaheuristic approach to multiobjective portfolio selection (340 citations)
- A Graph-based Ant system and its convergence (324 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Mathematical optimization, Metaheuristic, Ant colony optimization algorithms, Stochastic optimization and Operations research.
His research combines Algorithm and Mathematical optimization.
His study looks at the relationship between Metaheuristic and topics such as Project portfolio management, which overlap with Management science and Selection.
His biological study spans a wide range of topics, including Simulated annealing, Parallel metaheuristic, Meta-optimization, Graph and Swarm intelligence.
In his study, which falls under the umbrella issue of Stochastic optimization, Business process is strongly linked to Branch and bound.
His studies in Operations research integrate themes in fields like Genetic algorithm, Greedy algorithm and Weighted arithmetic mean.
He most often published in these fields:
- Mathematical optimization (55.66%)
- Metaheuristic (25.47%)
- Ant colony optimization algorithms (20.75%)
What were the highlights of his more recent work (between 2013-2021)?
- Mathematical optimization (55.66%)
- Humanitarian Logistics (8.49%)
- Multi-objective optimization (14.15%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Mathematical optimization, Humanitarian Logistics, Multi-objective optimization, Stochastic optimization and Stochastic programming.
His Mathematical optimization research includes themes of Schedule and Decomposition.
His Humanitarian Logistics study integrates concerns from other disciplines, such as Microeconomics, Minification and Operations research.
In his research, Discrete event simulation is intimately related to Metaheuristic, which falls under the overarching field of Operations research.
His Multi-objective optimization course of study focuses on Stochastic dominance and Stochastic modelling and Probabilistic-based design optimization.
The Stochastic optimization study combines topics in areas such as Dynamic decision-making, Function and Global optimization.
Between 2013 and 2021, his most popular works were:
- A math-heuristic for the warehouse location-routing problem in disaster relief (147 citations)
- Multicriteria optimization in humanitarian aid (111 citations)
- Stochastic multi-objective optimization: a survey on non-scalarizing methods (77 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Mathematical optimization
- Algorithm
Walter J. Gutjahr focuses on Humanitarian Logistics, Multi-objective optimization, Mathematical optimization, Operations research and Natural disaster.
The various areas that Walter J. Gutjahr examines in his Humanitarian Logistics study include Microeconomics, Equity, Management science and Minification.
Walter J. Gutjahr combines subjects such as Decision problem, Stochastic dominance and Probabilistic-based design optimization with his study of Multi-objective optimization.
His Mathematical optimization study frequently draws connections to other fields, such as Constraint.
His Operations research research integrates issues from Orienteering, Constraint, Decision support system, Theory of computation and Evolutionary algorithm.
His Stochastic programming research is multidisciplinary, incorporating perspectives in Multiple-criteria decision analysis, Stochastic modelling and Stochastic optimization.
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