Approximate Strip Packing - Foundations of Computer Science, 1996. Proceedings., 37th Annual Symposium on

Fault Tolerant Data Structures - Foundations of Computer Science, 1996. Proceedings., 37th Annual Symposium on

We consider the tolerance of data structures to memory faults. We observe that many pointer-based data structures (e.g. linked lists, trees, etc.) are highly nonresilient to faults. A single fault in a linked list or tree may result in the loss of the entire set of data. In this paper we present a formal framework for studying the fault tolerance properties of pointer-based data structures, and...

Communication-optimal maintenance of replicated information - Foundations of Computer Science, 1990. Proceedings., 31st Annual Symposium on

A new metaheuristic genetic-based placement algorithm for 2D strip packing

Given a container of fixed width, infinite height and a set of rectangular block, the 2D-strip packing problem consists of orthogonally placing all the rectangles such that the height is minimized. The position is subject to confinement of no overlapping of blocks. The problem is a complex NP-hard combinatorial optimization, thus a heuristic based on genetic algorithm is proposed to solve it. I...

Finding separator cuts in planar graphs within twice the optimal

A factor 2 approximation algorithm for the problem of finding a minimum-cost bbalanced cut in planar graphs is presented, for b ≤ 1 3 . We assume that the vertex weights are given in unary; for the case of binary vertex weights, a pseudoapproximation algorithm is presented. This problem is of considerable practical significance, especially in VLSI design. The natural algorithm for this problem ...

Improved Lower Bounds for Embeddings into L

We improve upon recent lower bounds on the minimum distortion of embedding certain finite metric spaces into L1. In particular, we show that for every n ≥ 1, there is an n-point metric space of negative type that requires a distortion of Ω(log log n) for such an embedding, implying the same lower bound on the integrality gap of a well-known semidefinite programming relaxation for sparsest cut. ...