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Sequencing and scheduling : algorithms and complexity

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TLDR
A survey of deterministic machine scheduling can be found in this article, where complexity results and optimization and approximation algorithms for problems involving a single machine, parallel machines, open shops, flow shops and job shops are presented.
Abstract
Sequencing and scheduling as a research area is motivated by questions that arise in production planning, in computer control, and generally in all situations in which scarce resources have to be allocated to activities over time. In this survey, we concentrate on the area of deterministic machine scheduling. We review complexity results and optimization and approximation algorithms for problems involving a single machine, parallel machines, open shops, flow shops and job shops. We also pay attention to two extensions of this area: resource-constrained project scheduling and stochastic machine scheduling.

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Journal ArticleDOI

Robust scheduling of a two-machine flow shop with uncertain processing times

TL;DR: A measure of schedule robustness that explicitly considers the risk of poor system performance over all potential realizations of job processing times is presented and results indicate that robust schedules provide effective hedges against processing time uncertainty while maintaining excellent expected makespan performance.
Journal ArticleDOI

Solving Parallel Machine Scheduling Problems by Column Generation

TL;DR: This work considers a class of problems of scheduling n jobs on m identical, uniform, or unrelated parallel machines with an objective of minimizing an additive criterion and proposes a decomposition approach for solving these problems exactly, indicating that this approach is promising and capable of solving large problems.
Proceedings ArticleDOI

Optimizing schedules for prioritized path planning of multi-robot systems

TL;DR: The experimental results demonstrate that the method is able to greatly reduce the number of failures and to significantly reduce the overall path length for different prioritized and decoupled path planning techniques and even for large teams of robots.
Journal ArticleDOI

Approximation in stochastic scheduling: the power of LP-based priority policies

TL;DR: A polyhedral relaxation of the performance space of stochastic parallel machine scheduling is presented, which generalizes previous results from deterministic scheduling and shows that all employed LPs can be solved in polynomial time by purely combinatorial algorithms.
Book ChapterDOI

A classification scheme for project scheduling

TL;DR: A wide and steadily growing variety of problem types which motivates the introduction of a systematic notation that can serve as a basis for a classification scheme are described.