Open Access
Sequencing and scheduling : algorithms and complexity
Eugene L. Lawler,Jan Karel Lenstra,Ahg Alexander Rinnooy Kan,David B. Shmoys +3 more
- Vol. 4, pp 445
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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.read more
Citations
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Book ChapterDOI
Differential Evolution for the Flow Shop Scheduling Problem
TL;DR: The classical problem of scheduling n jobs on m machines in a flow shop is to minimize the throughput time of all the jobs under the assumption that all jobs are processed on all machines at the same sequence.
Book ChapterDOI
The Lazy Bureaucrat Scheduling Problem
TL;DR: A new class of scheduling problems in which the optimization is performed by the worker (single "machine") who performs the tasks, which is called "Lazy Bureaucrat Problems" and gives rise to a rich set of new questions that explore the distinction between maximization and minimization in computing optimal schedules.
Journal ArticleDOI
Single-machine scheduling to minimize the weighted number of early and tardy agreeable jobs
TL;DR: This work considers a single-machine scheduling problem in which every job has a given target start time and a due-date, and shows that the problem is NP-complete in the strong sense.
Modelling collaborative planning and scheduling scenarios that include human and computer decision activities
TL;DR: In this paper, the authors place collaborative planning and scheduling within a systems-thinking context and show that human experts at the task control level are fundamental controllers of operations and coordinators of activities.
Book ChapterDOI
Online optimization of busy time on parallel machines
TL;DR: This study considers the following online scheduling problem in which the input consists of n jobs to be scheduled on identical machines of bounded capacity g (the maximum number of jobs that can be processed simultaneously on a single machine), and shows a large lower bound on the competitive ratio for general instances.