This paper presents three techniques for using an iterated local search algorithm to improve the performance of a state-of-the-art branch and bound algorithm for job shop scheduling. We use iterated local search to obtain (i) sharpened upper bounds, (ii) an improved branchordering heuristic, and (iii) and improved variableselection heuristic. On randomly-generated instances, our hybrid of itera...

Greedy routing has drawn a lot of attention in research community. To our best knowledge, stretch factor has not been studied for greedy routing algorithms. In this paper, we propose a new greedy routing algorithm and take the initiative to evaluate its stretch factor. Our algorithm generalizes the algorithm presented in [1]. It embeds an n-vertex connected graph G(V,E) in a semi-metric space. ...

We examine the utility of the Large-Step Markov Chain (LSMC) technique [13], a variant of the iterated descent heuristic of Baum [2], for VLSI netlist bipartitioning. LSMC iteratively nds a local optimum solution according to some greedy search (in our case, the Fiduccia-Mattheyses heuristic) and then perturbs this local optimum via a \kick move" into the starting solution of the next greedy de...

In this paper we study the problem of on-line multicasting on directed graphs, and we demonstrate the competitiveness of a greedy algorithm in a worst case analysis. We prove that the greedy algorithm performs almost as well as any on-line algorithm: the greedy upper bound is very close to the lower bound of any on-line algorithm. First, we improve on the upper bound of the oo-line greedy algor...