What is he best known for?
The fields of study he is best known for:
- Mathematical optimization
- Algorithm
- Artificial intelligence
His primary areas of study are Mathematical optimization, Metaheuristic, Tabu search, Optimization problem and Path.
Many of his research projects under Mathematical optimization are closely connected to Nonlinear programming, Quality and Context with Nonlinear programming, Quality and Context, tying the diverse disciplines of science together.
Rafael Martí has researched Metaheuristic in several fields, including GRASP, Genetic algorithm, Multi-objective optimization, Heuristic and Beam search.
His study in Tabu search is interdisciplinary in nature, drawing from both Heuristics, Local search, Distance matrix and Theoretical computer science.
The various areas that he examines in his Optimization problem study include Evolutionary algorithm, Linear ordering, Degree and Search algorithm.
His research investigates the connection between Path and topics such as Decision rule that intersect with problems in Range and Machine learning.
His most cited work include:
- Fundamentals of Scatter Search and Path Relinking (659 citations)
- Scatter Search: Methodology and Implementations in C (454 citations)
- Scatter Search and Local NLP Solvers: A Multistart Framework for Global Optimization (425 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Mathematical optimization, Metaheuristic, Tabu search, GRASP and Optimization problem.
His work in Mathematical optimization addresses subjects such as Path, which are connected to disciplines such as Decision rule.
His Metaheuristic study integrates concerns from other disciplines, such as Beam search and Global optimization.
His work in the fields of Guided Local Search overlaps with other areas such as Context.
His studies in GRASP integrate themes in fields like Graph, Integer programming and Cluster analysis.
In the field of Optimization problem, his study on Multi-swarm optimization overlaps with subjects such as Quality.
He most often published in these fields:
- Mathematical optimization (68.05%)
- Metaheuristic (52.07%)
- Tabu search (36.09%)
What were the highlights of his more recent work (between 2015-2021)?
- Mathematical optimization (68.05%)
- Metaheuristic (52.07%)
- Tabu search (36.09%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Mathematical optimization, Metaheuristic, Tabu search, Heuristics and GRASP.
His Mathematical optimization and Local search, Heuristic, Variable neighborhood search, Facility location problem and Combinatorial optimization problem investigations all form part of his Mathematical optimization research activities.
His Metaheuristic research is multidisciplinary, incorporating perspectives in Optimization problem and Data science.
Rafael Martí studies Guided Local Search which is a part of Tabu search.
The Heuristics study which covers Heuristic that intersects with Graph, Graph drawing and Theoretical computer science.
His GRASP research is multidisciplinary, incorporating elements of Path, Local search procedure and Descent.
Between 2015 and 2021, his most popular works were:
- Ant Colony Optimization: A Component-Wise Overview (28 citations)
- Advanced Greedy Randomized Adaptive Search Procedure for the Obnoxious p-Median problem ☆ (20 citations)
- Handbook of Heuristics (19 citations)
In his most recent research, the most cited papers focused on:
- Mathematical optimization
- Algorithm
- Artificial intelligence
His primary scientific interests are in Mathematical optimization, Metaheuristic, Local search, Tabu search and Heuristics.
His Mathematical optimization research is multidisciplinary, relying on both Crossover and GRASP.
His study in the field of Greedy randomized adaptive search procedure also crosses realms of Aggregate, Equity and Statistical dispersion.
His work in the fields of Metaheuristic, such as Variable neighborhood search, overlaps with other areas such as Software framework.
His Tabu search study combines topics from a wide range of disciplines, such as Bipartite graph, Graph drawing, Theoretical computer science and Heuristic.
His Heuristics research includes elements of Heuristic and Artificial intelligence.
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