His primary scientific interests are in Mathematical optimization, Heuristic, Combinatorial optimization, Algorithm and Ant colony optimization algorithms. Specifically, his work in Mathematical optimization is concerned with the study of Ant colony. His research integrates issues of Optimization problem and Heuristics in his study of Combinatorial optimization.
His Optimization problem research is multidisciplinary, incorporating elements of Simulated annealing and Artificial intelligence. His Ant colony optimization algorithms study combines topics from a wide range of disciplines, such as Parallel metaheuristic, Metaheuristic and Extremal optimization. His Extremal optimization research includes themes of Tabu search, Greedy algorithm, ANT, Artificial Ants and Premature convergence.
His main research concerns Mathematical optimization, Metaheuristic, Optimization problem, Heuristic and Combinatorial optimization. His Mathematical optimization research focuses on Algorithm and how it relates to Vehicle routing problem. His research investigates the connection between Metaheuristic and topics such as Tabu search that intersect with issues in Simulated annealing.
Vittorio Maniezzo has researched Optimization problem in several fields, including Lin–Kernighan heuristic and Artificial intelligence. His research investigates the connection between Ant colony optimization algorithms and topics such as Extremal optimization that intersect with problems in Premature convergence and Greedy algorithm. His study looks at the relationship between Quadratic assignment problem and fields such as Travelling salesman problem, as well as how they intersect with chemical problems.
His main research concerns Mathematical optimization, Metaheuristic, Operations research, Parallel computing and Warehouse. His Mathematical optimization research incorporates elements of Algorithm and Vehicle routing problem. His Vehicle routing problem research is multidisciplinary, incorporating perspectives in Lagrange multiplier, Set cover problem, Set and Core.
His research combines Population based and Metaheuristic. His research investigates the connection with Operations research and areas like Scheduling which intersect with concerns in Stochastic optimization. His studies deal with areas such as Cutting stock problem, Guided Local Search, Iterative method, Decomposition and Knapsack problem as well as Heuristics.
The scientist’s investigation covers issues in Mathematical optimization, Algorithm, Heuristic, Metaheuristic and Combinatorial optimization problem. His Mathematical optimization study incorporates themes from Core and Set. His Algorithm research integrates issues from Vehicle routing problem, Lagrangian relaxation and Heuristics.
His Heuristic study combines topics in areas such as Lagrange multiplier, Set cover problem, Knapsack problem, Relaxation and Nesting. Vittorio Maniezzo interconnects Dynamic programming, CUDA and Computational science in the investigation of issues within Combinatorial optimization problem.
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.
Ant system: optimization by a colony of cooperating agents
M. Dorigo;V. Maniezzo;A. Colorni.
systems man and cybernetics (1996)
Ant Colony Optimization
Vittorio Maniezzo;Luca Maria Gambardella;Fabio de Luigi.
Distributed Optimization by Ant Colonies
Alberto Colorni;Marco Dorigo;Vittorio Maniezzo;Francisco Varela.
european conference on artificial life (1992)
The ant system applied to the quadratic assignment problem
V. Maniezzo;A. Colorni.
IEEE Transactions on Knowledge and Data Engineering (1999)
Ant system for Job-shop Scheduling
Alberto Colorni;Marco Dorigo;Vittorio Maniezzo;Marco Trubian.
Belgian journal of operations research, statistics and computer science (1994)
Genetic evolution of the topology and weight distribution of neural networks
IEEE Transactions on Neural Networks (1994)
An Investigation of Some Properties of an Ant Algorithm
Alberto Colorni;Marco Dorigo;Vittorio Maniezzo;Reinhard Manner.
parallel problem solving from nature (1992)
Exact and Approximate Nondeterministic Tree-Search Procedures for the Quadratic Assignment Problem
Informs Journal on Computing (1999)
An Exact Algorithm for the Resource-Constrained Project Scheduling Problem Based on a New Mathematical Formulation
Aristide Mingozzi;Vittorio Maniezzo;Salvatore Ricciardelli;Lucio Bianco.
Management Science (1998)
Heuristics from Nature for Hard Combinatorial Optimization Problems
Alberto Colorni;Marco Dorigo;Francesco Maffioli;Vittorio Maniezzo.
International Transactions in Operational Research (1996)
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: