Add to ORKGA greedy heuristics to solve a given combinatorial optimisation problem can be seen as an element of an infinite set of heuristics, H, which is defined by a function that depends on several parameters. We propose a procedure for determining the best element of H for a set of instances of the combinatorial optimisation problem. The procedure consists essentially in applying a direct non-linear optimization algorithm to a function of the parameters that characterise H
This talk will present a tutorial on the implementation and use of metaheuristics and approximation ...
In this paper, we review parallel search techniques for approximating the global optimal solution of...
A greedy randomized adaptive search procedure (GRASP) is a metaheuristic for combinatorial optimizat...
A greedy heuristics to solve a given combinatorial optimisation problem can be seen as an element of...
This is the first book to cover GRASP (Greedy Randomized Adaptive Search Procedures), a metaheuristi...
In recent years, there have been many studies in which tailored heuristics and meta-heuristics have ...
AbstractPerhaps the best known algorithm in combinatorial optimization is the greedy algorithm. A na...
There are numerous combinatorial optimization problems, for which computing exact optimal solutions ...
We introduce a metaheuristic framework for combinatorial optimization. Our framework is similar to m...
The goal of this research is to develop a systematic, integrated method of designing efficient searc...
The use of meta-heuristics for solving combinatorial optimisation has now a long history, and there ...
... techniques for designing better search algorithms. Knowledge captured in designing one search al...
Available from British Library Document Supply Centre-DSC:DXN047342 / BLDSC - British Library Docume...
This paper shows that repeated application of a greedy approximation algorithm on some suitably sele...
Abstract- Research in combinatorial optimization initially focused on finding optimal solutions to v...
This talk will present a tutorial on the implementation and use of metaheuristics and approximation ...
In this paper, we review parallel search techniques for approximating the global optimal solution of...
A greedy randomized adaptive search procedure (GRASP) is a metaheuristic for combinatorial optimizat...
A greedy heuristics to solve a given combinatorial optimisation problem can be seen as an element of...
This is the first book to cover GRASP (Greedy Randomized Adaptive Search Procedures), a metaheuristi...
In recent years, there have been many studies in which tailored heuristics and meta-heuristics have ...
AbstractPerhaps the best known algorithm in combinatorial optimization is the greedy algorithm. A na...
There are numerous combinatorial optimization problems, for which computing exact optimal solutions ...
We introduce a metaheuristic framework for combinatorial optimization. Our framework is similar to m...
The goal of this research is to develop a systematic, integrated method of designing efficient searc...
The use of meta-heuristics for solving combinatorial optimisation has now a long history, and there ...
... techniques for designing better search algorithms. Knowledge captured in designing one search al...
Available from British Library Document Supply Centre-DSC:DXN047342 / BLDSC - British Library Docume...
This paper shows that repeated application of a greedy approximation algorithm on some suitably sele...
Abstract- Research in combinatorial optimization initially focused on finding optimal solutions to v...
This talk will present a tutorial on the implementation and use of metaheuristics and approximation ...
In this paper, we review parallel search techniques for approximating the global optimal solution of...
A greedy randomized adaptive search procedure (GRASP) is a metaheuristic for combinatorial optimizat...