## Info

Not surprisingly, the branch-and-bound algorithm by Neumann and Zimmermann (2002) seems to be more efficient than the earlier algorithm by De Reyck and Hcrroelen (19986). The improvement upon the latter algorithm is probably to be attributed to the tremendous difference in the time needed for solving the relaxations. The dual method typically runs in a small fraction of the time that is required for re-optimizing from scratch the minimizer with the primal steepest descent method after the...

## Convexifiable Objective Functions

For convexifiable objective functions, time-constrained project scheduling with disjunctive precedence constraints can no longer be performed efficiently, and thus resource conflicts are settled by introducing ordinary precedence constraints. After the treatment of an enumeration scheme for generating candidate schedules, we discuss two alternative approaches to solving the relaxations the primal approach, which will be used to solve the time-constrained project scheduling problem at the root...

## Maketo Order Production Scheduling

We consider the processing of a given set of customer orders in a multi-level make-to-order manufacturing environment, where no inventories are built up for future sale. At first, we recall some basic concepts from materials requirements planning (see, e.g., Nahmias 1997, Sect. 6.1). We assume that each final product consists of several subassemblies, which in turn may contain several components from lower production levels. Let pf be the set of all final products ordered and let P be the set...

## Applications

The present chapter is concerned with applications of the concepts developed in Chapters 1 to 5 to production planning problems in the manufacturing and process industries, to the evaluation of investment projects, and to resource allocation problems that are subject to different kinds of uncertainty. In Section 6.1 we discuss how scheduling problems arising in make-to-order assembly environments can be modelled as resource-constrained project scheduling problems. For different product...

## Introduction

Project management and resource allocation. A project is a major one-time undertaking dedicated to some well-defined objective and involving considerable money, personnel, and equipment. It is usually initiated either by some need of the parent organization or by a customer request. The life cycle of a project can be structured into five consecutive phases involving specific managerial tasks (cf. Klein 2000, Section 1.2). Starting with some proposal, several preliminary studies such as a...

## References

Aarts E, Lenstra JK (2003 a) Introduction. In Aarts E, Lenstra JK (eds) Local Search in Combinatorial Optimization. Princeton University Press, Princeton, pp 1-17 2. Aarts E, Lenstra JK, eds (20036) Local Search in Combinatorial Optimization. Princeton University Press, Princeton 3. Ahuja RK, Magnanti TL, Orlin JB (1993) Network Flows. Prentice Hall, En-glewood Cliffs 4. Aldowaisan T, Allahverdi A, Gupta JN (1999) A review of scheduling research involving setup considerations. Omega 27 219-239...

## Coping with Uncertainty

In this section we propose two deterministic strategies for coping with uncertainty in resource allocation problems. When executing a project, unforeseen downtimes of resources, staff time off, reworking time, late delivery of raw materials or bought-in parts, or imprecise time and resource estimations may cause considerable deviations from the schedule determined. Basically, there are two ways of taking uncertainty into account when performing the resource allocation. First, we may anticipate...