Add to ORKGIn this paper we observe the possibility to accelerate a search algorithm for multiobjective optimization problems with help of a graphics processing unit. Besides an implementation we present test results for it and the conclusions that can be drawn from these results
International audienceIn practice, combinatorial optimization problems are complex and computational...
In recent years, graphics processing units (GPUs) have emerged as a powerful architecture for solvin...
Every new desktop or laptop come equipped with a multicore, programmable graphic processing unit (GP...
General purpose graphical processing units were proven to be useful for accelerating computationally...
A* search is a fundamental topic in artificial intelligence. Recently, the general purpose computat...
Most of the problems of discrete optimization belong to the class of NP-complete problems. This mean...
Metaheuristics is a class of approximate methods based on heuristics that can effectively handle rea...
Nowadays Personal Computers (PCs) are often equipped with powerful, multi-core CPU. However, the pro...
There are many combinatorial optimization problems such as traveling salesman problem, quadratic-ass...
International audienceMultiobjective local search algorithms are efficient methods to solve complex ...
Abstract. We present a GPU algorithm for the nearest neighbor search, an important database problem....
We present a GPU algorithm for the nearest neighbor search, an important database problem. The searc...
Graphics processor units (GPUs) are many-core processors that perform better than central processing...
Thesis deals with discrete optimization problems. It focusses on faster ways to find good solutions ...
AbstractMetaheuristics is a class of approximate methods based on heuristics that can effectively ha...
International audienceIn practice, combinatorial optimization problems are complex and computational...
In recent years, graphics processing units (GPUs) have emerged as a powerful architecture for solvin...
Every new desktop or laptop come equipped with a multicore, programmable graphic processing unit (GP...
General purpose graphical processing units were proven to be useful for accelerating computationally...
A* search is a fundamental topic in artificial intelligence. Recently, the general purpose computat...
Most of the problems of discrete optimization belong to the class of NP-complete problems. This mean...
Metaheuristics is a class of approximate methods based on heuristics that can effectively handle rea...
Nowadays Personal Computers (PCs) are often equipped with powerful, multi-core CPU. However, the pro...
There are many combinatorial optimization problems such as traveling salesman problem, quadratic-ass...
International audienceMultiobjective local search algorithms are efficient methods to solve complex ...
Abstract. We present a GPU algorithm for the nearest neighbor search, an important database problem....
We present a GPU algorithm for the nearest neighbor search, an important database problem. The searc...
Graphics processor units (GPUs) are many-core processors that perform better than central processing...
Thesis deals with discrete optimization problems. It focusses on faster ways to find good solutions ...
AbstractMetaheuristics is a class of approximate methods based on heuristics that can effectively ha...
International audienceIn practice, combinatorial optimization problems are complex and computational...
In recent years, graphics processing units (GPUs) have emerged as a powerful architecture for solvin...
Every new desktop or laptop come equipped with a multicore, programmable graphic processing unit (GP...