What is he best known for?
The fields of study he is best known for:
- Mathematical optimization
- Linear programming
- Algorithm
His scientific interests lie mostly in Mathematical optimization, Algorithm, Fractional programming, Numerical analysis and Weapon target assignment problem.
Jacques A. Ferland studies Simulated annealing, a branch of Mathematical optimization.
His work is dedicated to discovering how Algorithm, Convergence are connected with Generalized fractional programming and Nonlinear programming and other disciplines.
His studies in Numerical analysis integrate themes in fields like Differentiable function and Order.
Jacques A. Ferland interconnects Transportation planning and Guided Local Search in the investigation of issues within Weapon target assignment problem.
His study in the fields of Linear bottleneck assignment problem under the domain of Generalized assignment problem overlaps with other disciplines such as Genetic operator.
His most cited work include:
- Genetic and hybrid algorithms for graph coloring (281 citations)
- Genetic Hybrids for the Quadratic Assignment Problem. (203 citations)
- Algorithms for generalized fractional programming (195 citations)
What are the main themes of his work throughout his whole career to date?
Jacques A. Ferland spends much of his time researching Mathematical optimization, Operations research, Algorithm, Tabu search and Scheduling.
His Mathematical optimization research focuses on Generalized assignment problem, Simulated annealing, Metaheuristic, Heuristic and Guided Local Search.
His Operations research research focuses on Dynamic priority scheduling and how it connects with Fair-share scheduling.
His Algorithm research incorporates themes from Convergence, Fractional programming and Benchmark.
His Fractional programming study integrates concerns from other disciplines, such as Linear-fractional programming, Numerical analysis and Applied mathematics.
His work in Scheduling addresses issues such as Simulation, which are connected to fields such as Generator and Vehicle routing problem.
He most often published in these fields:
- Mathematical optimization (56.63%)
- Operations research (20.48%)
- Algorithm (16.87%)
What were the highlights of his more recent work (between 2006-2019)?
- Mathematical optimization (56.63%)
- Algorithm (16.87%)
- Metaheuristic (7.23%)
In recent papers he was focusing on the following fields of study:
His main research concerns Mathematical optimization, Algorithm, Metaheuristic, Genetic algorithm and Open-pit mining.
Tabu search, Generalized assignment problem, Weapon target assignment problem, Heuristic and Swarm behaviour are the primary areas of interest in his Mathematical optimization study.
The concepts of his Weapon target assignment problem study are interwoven with issues in Nurse scheduling problem and Exact algorithm.
In general Algorithm, his work in Local search is often linked to Cell formation linking many areas of study.
His study in Metaheuristic is interdisciplinary in nature, drawing from both Single objective and Scheduling.
The various areas that he examines in his Genetic algorithm study include Simulated annealing and Hill climbing.
Between 2006 and 2019, his most popular works were:
- A variable neighbourhood descent algorithm for the open-pit mine production scheduling problem with metal uncertainty (38 citations)
- A hybrid method based on linear programming and variable neighborhood descent for scheduling production in open-pit mines (33 citations)
- An exact method with variable fixing for solving the generalized assignment problem (29 citations)
In his most recent research, the most cited papers focused on:
- Mathematical optimization
- Linear programming
- Algorithm
His primary areas of investigation include Mathematical optimization, Open-pit mining, Algorithm, Variable and Descent algorithm.
His works in Multiple constraints, Heuristic, Weapon target assignment problem and Beam search are all subjects of inquiry into Mathematical optimization.
His work deals with themes such as Linear programming and Scheduling, which intersect with Multiple constraints.
His Heuristic research is multidisciplinary, incorporating elements of Branch and cut and Benchmark.
Jacques A. Ferland has researched Weapon target assignment problem in several fields, including Lagrangian relaxation, Decision problem and Dynamic programming.
His Beam search research includes elements of Local search, Guided Local Search, Genetic algorithm and Hill climbing.
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