Minimizing average flow time on unrelated machines

We give an O(Q)-approximation for minimizing average flow time on unrelated machines, where Q is the maximum number of different process times on a machine. Consequently, the ratio is O(logP/loge) if all process times are a power of e. Here, P is the ratio of the maximum and minimum process time of a job

Two NP-hardness results for preemptive minsum scheduling of unrelated parallel machines

We show that the problems of minimizing total completion time and of minimizing the number of late jobs on unrelated parallel machines, when preemption is allowed, are both NP-hard in the strong sense. The former result settles a long-standing open question

The generalized two-server problem

We consider the generalized on-line two-server problem in which each server moves in its own metric space. Requests for service arrive one-by-one and every request is represented by two points: one in each metric space. The problem is to move, at every request, one of the two servers to its request-point such that the total distance travelled by the two servers is minimized.The special case in which both metric spaces are the real line is known as the CNN-problem. It has been a well-known open question in on-line optimization if an algorithm with a constant-competitive ratio exists for this problem. We answer this question in the affirmative by providing a constant-competitive algorithm for the generalized two-server problem on any metric space.The basic result in this article is a characterization of competitiveness for metrical service systems that seems much easier to use when looking for a competitive algorithm. The existence of a competitive algorithm for the generalized two-server problem follows rather easily from this result

Approximation algorithms for the Euclidean traveling salesman problem with discrete and continuous neighborhoods

In the Euclidean traveling salesman problem with discrete neighborhoods, we are given a set of points P in the plane and a set of n connected regions (neighborhoods), each containing at least one point of P. We seek to find a tour of minimum length which visits at least one point in each region. We give (i) an O(a)-approximation algorithm for the case when the regions are disjoint and a-fat, with possibly varying size; (ii) an O(a3)-approximation algorithm for intersecting a-fat regions with comparable diameters. These results also apply to the case with continuous neighborhoods, where the sought TSP tour can hit each region at any point. We also give (iii) a simple O(log n)-approximation algorithm for continuous non-fat neighborhoods. The most distinguishing features of these algorithms are their simplicity and low running-time complexities

On-line dial-a-ride problems under a restricted information model

In on-line dial-a-ride problems, servers are traveling in some metric space to serve requests for rides which are presented over time. Each ride is characterized by two points in the metric space, a source, the starting point of the ride, and a destination, the end point of the ride. Usually it is assumed that at the release of such a request complete information about the ride is known. We diverge from this by assuming that at the release of such a ride only information about the source is given. At visiting the source, the information about the destination will be made available to the servers. For many practical problems, our model is closer to reality. However, we feel that the lack of information is often a choice, rather than inherent to the problem: additional information can be obtained, but this requires investments in information systems. In this paper we give mathematical evidence that for the problem under study it pays to invest

International record of medicine and general practice clinics

In dial-a-ride problems, items have to be transported from a source to a destination. The characteristics of the servers involved as well as the specific requirements of the rides may vary. Problems are defined on some metric space, and the goal is to find a feasible solution that minimizes a certain objective function. The structure of these problems allows for a notation similar to the standard notation for scheduling and queueing problems. We introduce such a notation and show how a class of 7,930 dial-a-ride problem types arises from this approach. In examining their computational complexity, we define a partial ordering on the problem class and incorporate it in the computer program DARCLASS. As input DARCLASS uses lists of problems whose complexity is known. The output is a classification of all problems into one of three complexity classes: solvable in polynomial time, NP-hard, or open. For a selection of the problems that form the input for DARCLASS, we exhibit a proof of polynomial-time solvability or NP-hardnes