Sensitivity Analysis of List Scheduling Heuristics

When jobs have to be processed on a set of identical parallel machines so as to minimize the makespan of the schedule, list scheduling rules form a popular class of heuristics. The order in which jobs appear on the list is assumed here to be determined by the relative size of their processing times; well known special cases are the LPT rule and the SPT rule, in which the jobs are ordered according to non-increasing and non-decreasing processing time respectively. When one of the job processing times is gradually increased, the schedule produced by a list scheduling rule will be affected in a manner reflecting its sensitivity to data perturbations. We analyze this phenomenon and obtain analytical support for the intuitively plausible notion that the sensitivity of a list scheduling rule increases with the quality of the schedule produced

Branch-and-Bound Algorithms for the Test Cover Problem

In the test cover problem a set of items is given together with a collection of subsets of the items, called tests. A smallest subcollection of tests is to be selected such that for every pair of items there is a test in the selection that contains exactly one of the two items. This problem is NP-hard in general. It has important applications in biology, pharmacy, and the medical sciences, as well as in coding theory. We develop a variety of branch-and-bound algorithms to solve the problem to optimality. The variety is in the definition of the branching rules and the lower bounds to prune the search tree. Our algorithms are compared both theoretically and empirically