Topic
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.
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TL;DR: It is claimed that a single machine scheduling problem of minimizing the number of late jobs with a positional learning effect is strongly NP-hard, and a reduction from 3-PARTITION to the decision version of this problem is provided, but the proof is incorrect.
Abstract: In the paper Lin (2007), it is claimed that a single machine scheduling problem of minimizing the number of late jobs with a positional learning effect is strongly NP-hard. To prove it, the author ...
20 citations
TL;DR: This paper proposes branch-and-bound (B&B) methods to derive the optimal sequences for general past-sequence-dependent (psd) setup time and log-linear learning in which the setup times and learning effects are job-dependent.
Abstract: This paper deals with a single machine scheduling problem with general past-sequence-dependent (psd) setup time and log-linear learning in which the setup times and learning effects are job-dependent. The setup times are unique functions of the length of already processed jobs, and the learning effects show that processing times are unique decreasing functions of job positions. The goal is to find the optimal sequences that minimise objective functions such as the makespan, total completion time, total lateness, total waiting cost, total waiting time, total absolute differences in completion times, and the sum of earliness, tardiness and common due date penalty. Special cases of the resulting problems are solvable in polynomial time; however, the general problems are difficult to solve. We propose branch-and-bound (B&B) methods to derive the optimal sequences for such problems. Computational results show that the proposed methods can solve relatively large problem instances in reasonable amounts of time.
20 citations
TL;DR: An integrated model is proposed that coordinates preventive maintenance planning with single-machine scheduling to minimize the weighted completion time of jobs and maintenance cost, simultaneously.
Abstract: Production scheduling and maintenance planning are two interdependent issues that most often have been investigated independently. Although both preventive maintenance (PM) and minimal repair affect availability and failure rate of a machine, only a few researchers have considered this interdependency in the literature. Furthermore, most of the existing joint production and preventive maintenance scheduling methods assume that machine is available during the planning horizon and consider only a possible level for PM. In this research, an integrated model is proposed that coordinates preventive maintenance planning with single-machine scheduling to minimize the weighted completion time of jobs and maintenance cost, simultaneously. This paper not only considers multiple PM levels with different costs, times and reductions in the hazard rate of the machine, but also assumes that a machine failure may occur at any time. To illustrate the effectiveness of the suggested method, it is compared to two situations of no PM and a single PM level. Eventually, to tackle the suggested problem, multi-objective particle swarm optimization and non-dominated sorting genetic algorithm (NSGA-II) are employed and their parameters are tuned Furthermore, their performances are compared in terms of three metrics criteria.
20 citations
TL;DR: This paper is the first successful attempt to develop a constant ratio approximation algorithm for this problem and presents two approaches to designing such an algorithm.
20 citations
TL;DR: A scheduling problem in which n jobs are grouped into F groups and are to be processed on a single machine to find an optimal commonDue date and an optimal sequence of jobs to minimize the sum of the cost of tardy jobs and the cost related to the common due date.
20 citations