Scheduling under Uncertainty: Optimizing Against a Randomizing Adversary

Deterministic models for project scheduling and control suffer from the fact that they assume complete information and neglect random influences that occur during project execution. A typical consequence is the underestimation of the expected project duration and cost frequently observed in practice. To cope with these phenomena, we consider scheduling models in which processing times are random but precedence and resource constraints are fixed. Scheduling is done by policies which consist of an online process of decisions that are based on the observed past and the a priori knowledge of the distribution of processing times. We give an informal survey on different classes of policies and show that suitable combinatorial properties of such policies give insight into optimality, computational methods, and their approximation behavior. In particular, we present recent constant-factor approximation algorithms for simple policies in machine scheduling that are based on a suitable polyhedral relaxation of the performance space of policies

Information on MIPLIB's timetab-instances

This report provides information for the timetab-instances of the MIPLIB. This includes data for both, the underlying real-world application and the resulting graph problem

Scheduling Scarce Resources in Chemical Engineering

The efficient utilization of scarce resources, such as machines or manpower, is major challenge within production planning in the chemical industry. We describe solution methods for a resource-constrained scheduling problem which arises at a production facility at BASF AG in Ludwigshafen. We have developed and implemented two different algorithms to solve this problem, a novel approach which is based upon Lagrangian relaxation, as well as a branch-and-bound procedure. Since the Lagrangian approach is applicable for a whole variety of resource-constrained scheduling problems, it is of interest not only for the specific problem we describe, but is of interest also for many other industrial applications. In this paper, we describe both approaches, and also report on computational results, based upon practical problem instances as well as benchmark test sets

A Case Study in Periodic Timetabling

In the overwhelming majority of public transportation companies, designing a periodic timetable is even nowadays largely performed manually. Software tools only support the planners in evaluating a periodic timetable, or by letting them comfortably shift sets of trips by some minutes, but they rarely use optimization methods. One of the main arguments against optimization is that there is no clear objective in practice, but that many criteria such as amount of rolling stock required, average passenger changing time, average speed of the trains, and the number of cross-wise correspondences have to be considered

A Note on Scheduling Problems with Irregular Starting Time Costs

In [9], Maniezzo and Mingozzi study a project scheduling problem with irregular starting time costs. Starting from the assumption that its computational complexity status is open, they develop a branch-and-bound procedure, and identify special cases that are solvable in polynomial time. In this note, we review three previously established, related results which show that the general problem is solvable in polynomial time

Scheduling Series-Parallel Orders Subject to 0/1-Communication Delays

We consider the problem P}&;| prec},cij&;{0,1}|κ of scheduling jobs with arbitrary processing times on sufficiently many parallel processors subject to series-parallel precedence constraints and 0/1-communication delays in order to minimize a regular performance measure κ. Such schedules without processor restrictions are used for generating approximate solutions for a restricted number of processors

Scheduling with AND/OR precedence constraints

In many scheduling applications it is required that the processing of some job must be postponed until some other job, which can be chosen from a pre-given set of alternatives, has been completed. The traditional concept of precedence constraints fails to model such restrictions. Therefore, the concept has been generalized to so-called AND/OR precedence constraints which can cope with this kind of requirement

Minimizing Total Delay in Fixed-Time Controlled Traffic Networks

We present two different approaches to minimize total delay in signalized fixed-time controlled inner city traffic networks. Firstly, we develop a time discrete model where all calculations are done pathwise and vehicles move on "time trajectories" on their routes. Secondly, an idea by Gartner, Little, and Gabbay is extended to a continuous, linkwise operating model using "Link Performance Functions" to determine delays. Both models are formulated as mixed-integer linear programs and are compared and evaluated by PTV AG's simulation tool VISSIM 3.70