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 shown that under special conditions the presented algorithm may be used when preemption is not allowed and there are precedence constraints and ready times of jobs.
30 citations
TL;DR: It is proved that the two algorithms employed to solve the single machine scheduling problem with periodic maintenance have the same worst cast ratio under different confidence levels and the LPT algorithm has a better performance bound.
Abstract: This paper studies a single machine scheduling problem with periodic maintenance, in which processing time and repair time are nondeterministic. In order to deal with nondeterministic phenomena, uncertainty theory is introduced to minimize the makespan under an uncertain environment. Three uncertain programming models are proposed, which can be converted into deterministic forms based on the uncertainty inverse distribution. List scheduling (LS) and longest processing time (LPT) algorithms are employed to solve the problem. It is proved that the two algorithms have the same worst cast ratio under different confidence levels and the LPT algorithm has a better performance bound. A hybrid intelligent algorithm for the problem is designed and some numerical experiments demonstrate the effectiveness of the proposed models and algorithm.
30 citations
TL;DR: It is proved that the general case with identical parallel machines and a given set of assignable due dates where the cardinality of this set is bounded by a constant number is still polynomially solvable.
30 citations
TL;DR: The computational results on 320 benchmark instances show that the proposed DQGA is comparable to the state-of-the-art methods in the literature and outperforms the existing methods for some instances, as could improve the reported “best-known solutions” in notably less time.
30 citations
TL;DR: An integrated optimization model of production planning and scheduling for a three-stage manufacturing system composed of a forward chain of three kinds of workshops: a job shop, a parallel flow shop consisting of parallel production lines, and a single machine shop is presented.
Abstract: This paper presents an integrated optimization model of production planning and scheduling for a three-stage manufacturing system, which is composed of a forward chain of three kinds of workshops: a job shop, a parallel flow shop consisting of parallel production lines, and a single machine shop. As the products at the second stage are assembled from the parts produced in its upstream workshop, a complicated production process is involved. On the basis of the analysis of the batch production, a dynamic batch splitting and amalgamating algorithm is proposed. Then, a heuristic algorithm based on a genetic algorithm (known as the integrated optimization algorithm) is proposed for solving the problem. Note to Practitioners-This paper presents a method for integrated production planning and scheduling in a three-stage manufacturing system consisting of a forward chain of three kinds of workshops, which is common in such enterprises as producers of automobiles and household electric appliances, as in the case of an autobody plant usually with the stamping workshop, the welding and assembling workshop, and the painting workshop. Herein, the production planning and scheduling problems are simultaneously addressed in the way that a feasible production plan can be obtained and the inventory reduced. A batch splitting and amalgamating algorithm is proposed for balancing the production time of the production lines. And a case study of the integrated planning and scheduling problem in a real autobody plant verifies the effectiveness of our method
30 citations