Add to ORKGAbstract The relative worst-order ratio is a measure of the quality of online algorithms. In contrast to the competitive ratio, this measure compares two online algorithms directly instead of using an intermediate comparison with an optimal offline algorithm. In this paper, we apply the relative worst-order ratio to online algorithms for several common variants of the bin packing problem. We mainly consider pairs of algorithms that are not dis-tinguished by the competitive ratio and show that the relative worst-order ratio prefers the intuitively better algorithm of each pair
We revisit the classic online bin packing problem studied in the half-century. In this problem, item...
AbstractWe follow the work of [G. Gutin, T. Jensen, A. Yeo, On-line bin packing with two item sizes,...
We study the online bin packing problem under two stochastic settings. In the bin packing problem, w...
AbstractThe relative worst-order ratio, a relatively new measure for the quality of on-line algorith...
Best-fit is the best known algorithm for on-line bin-packing, in the sense that no algorithm is know...
We consider two new online bin packing problems, the online Variable Cost and Size Bin Packing Probl...
We use game theory techniques to automatically compute improved lower bounds on the competitive rati...
In competitive analysis, we usually do not put any restrictions on the computational complexity of o...
Abstract. In the bin packing problem we are given an instance consist-ing of a sequence of items wit...
AbstractOn-line algorithms have been extensively studied for the one-dimensional bin packing problem...
textabstractIn this paper we discuss lower bounds for the asymptotic worst case ratio of on-line alg...
AbstractThe classical bin packing problem is one of the best-known and most widely studied problems ...
URL des Cahiers : http://mse.univ-paris1.fr/MSEFramCahier2006.htmCahiers de la Maison des Sciences E...
We improve the lower bound on the asymptotic competitive ratio of any online algorithm for bin packi...
Abstract. In this paper, we study the advice complexity of the online bin packing problem. In this w...
We revisit the classic online bin packing problem studied in the half-century. In this problem, item...
AbstractWe follow the work of [G. Gutin, T. Jensen, A. Yeo, On-line bin packing with two item sizes,...
We study the online bin packing problem under two stochastic settings. In the bin packing problem, w...
AbstractThe relative worst-order ratio, a relatively new measure for the quality of on-line algorith...
Best-fit is the best known algorithm for on-line bin-packing, in the sense that no algorithm is know...
We consider two new online bin packing problems, the online Variable Cost and Size Bin Packing Probl...
We use game theory techniques to automatically compute improved lower bounds on the competitive rati...
In competitive analysis, we usually do not put any restrictions on the computational complexity of o...
Abstract. In the bin packing problem we are given an instance consist-ing of a sequence of items wit...
AbstractOn-line algorithms have been extensively studied for the one-dimensional bin packing problem...
textabstractIn this paper we discuss lower bounds for the asymptotic worst case ratio of on-line alg...
AbstractThe classical bin packing problem is one of the best-known and most widely studied problems ...
URL des Cahiers : http://mse.univ-paris1.fr/MSEFramCahier2006.htmCahiers de la Maison des Sciences E...
We improve the lower bound on the asymptotic competitive ratio of any online algorithm for bin packi...
Abstract. In this paper, we study the advice complexity of the online bin packing problem. In this w...
We revisit the classic online bin packing problem studied in the half-century. In this problem, item...
AbstractWe follow the work of [G. Gutin, T. Jensen, A. Yeo, On-line bin packing with two item sizes,...
We study the online bin packing problem under two stochastic settings. In the bin packing problem, w...