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Single-machine scheduling

About: Single-machine scheduling is a research topic. Over the lifetime, 2473 publications have been published within this topic receiving 56288 citations.


Papers
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Proceedings ArticleDOI
10 Oct 2005
TL;DR: This paper constructs innovative hybrid techniques that incorporate the best of Lagrangian relaxation and Tabu search solution approaches to solve the daily imaging scheduling problem for the newest generation of low-orbit, earth observation satellite, FORMOSAT-2.
Abstract: This paper presents the research and development of the hybridization of a mathematical programming approach with a promising evolution on the daily imaging scheduling problem for the newest generation of low-orbit, earth observation satellite, FORMOSAT-2. This NP-hard satellite scheduling problem belongs to a class of single-machine scheduling problems with salient features of job-assembly characteristic, sequence-dependent setup effect, and constraint of operating time window. We construct innovative hybrid techniques that incorporate the best of Lagrangian relaxation and Tabu search solution approaches to solve this scheduling problem. Numerical results demonstrate that the proposed hybrid algorithms are effective and efficient in applications to the real problems.

29 citations

Journal ArticleDOI
TL;DR: It is shown that even with the introduction of learning effect and deteriorating jobs to job processing times, single machine makespan and sum of completion times minimization problems remain polynomially solvable, respectively.

29 citations

Journal ArticleDOI
TL;DR: This paper is concerned with scheduling of a marketing-production system in which the demand rate changes in accordance with marketing actions, and the structure of the hedging-point policy is fully analyzed.
Abstract: This paper is concerned with scheduling of a marketing-production system in which the demand rate changes in accordance with marketing actions. Our goal is to provide illuminating descriptions and insight on the optimal control policies. A basic building-block model involving a single machine is developed. The objective is to choose the rates of production and marketing to maximize the overall profit. Consisting of a pair of hedging points, the optimal policy is attractive in practice because of its simplicity and can be computed by solving algebraic equations. Aiming at obtaining analytic solutions, various control regions of the optimal policy are depicted; the structure of the hedging-point policy is fully analyzed.

29 citations

Journal ArticleDOI
TL;DR: This work designs a range of polynomial-time solution algorithms that enable the decision-maker to determine possible sequences of jobs and MPs in the schedule, so that the makespan objective can be minimized.
Abstract: We study single machine scheduling problems with linear time-dependent deterioration effects and maintenance activities. Maintenance periods (MPs) are included into the schedule, so that the machine, that gets worse during the processing, can be restored to a better state. We deal with a job-independent version of the deterioration effects, that is, all jobs share a common deterioration rate. However, we introduce a novel extension to such models and allow the deterioration rates to change after every MP. We study several versions of this generalized problem and design a range of polynomial-time solution algorithms that enable the decision-maker to determine possible sequences of jobs and MPs in the schedule, so that the makespan objective can be minimized. We show that all problems reduce to a linear assignment problem with a product matrix and can be solved by methods very similar to those used for solving problems with positional effects.

29 citations

Journal ArticleDOI
TL;DR: This paper considers the problem of finding a nonpreemptive schedule for a single machine to minimize the maximum lateness with release dates and precedence constraints and develops a branch and bound algorithm.

29 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202333
202270
202188
202083
201972
201889