Schedule-an expert-like system for machine scheduling

Lamatsch, Achim; Morlock, Martin; Neumann, Klaus; Rubach, Thomas

doi:10.1007/bf02283757

Cited by 16 publications

(5 citation statements)

References 3 publications

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“…The rest of the tools usually leave to the user the choice of the most suitable model (see Pinedo and Yen (1997); ) or, in the simplest cases, only one specific model can be used (Ko and Wang, 2010), therefore making the tool hardly usable if any change takes place in the scheduling process. Among the works implementing Model Detection, the approaches are summarised in Table 2, ranging from those using Reduction Trees (RT) (Lamatsch et al, 1988), those using Decision Trees (DT) (Wang and Lin, 1997;Metaxiotis et al, 2002), and those that can detect the layout from raw data (T'kindt et al, 2005;Yang and Lin, 2009).…”

Section: Problem Modellingmentioning

confidence: 99%

“…The incorporation of algorithms at the user level has had more acceptance within authors (7 tools (70%)). Lamatsch et al (1988); Angelidis et al (2011) use specific languages to add new algorithms (LBG), while CEA is adopted by Sauer (1993); Sauer and Bruns (1997); Sauer et al (1998). RIT can be found in Taunton and Ready (1994), where instead of pieces of algorithms, users can generate rules that can be added or removed as required.…”

Section: Problem Solvingmentioning

confidence: 99%

“…are late to ease the development of new algorithms (E) can be found inLamatsch et al (1988);Tang et al (2009);Zhang et al (2010). Finally, allowing the expert to enter new constraints obtained from his/her experience or from his/her knowledge on the field is implemented in…”

mentioning

confidence: 99%

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A review and classification of computer-based manufacturing scheduling tools

Dios

Framiñán

2016

Computers & Industrial Engineering

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Section: Problem Modellingmentioning

confidence: 99%

Section: Problem Solvingmentioning

confidence: 99%

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A review and classification of computer-based manufacturing scheduling tools

Dios

Framiñán

2016

Computers & Industrial Engineering

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“…When a scheduling decision is to be made, the adaptive scheduling system identi es the current state of manufacturing environments, searches for matching preconditions, and determines an appropriate scheduling rule for the decision-making. Lamatsch et al (1988) built a knowledge base that contained algorithms for solving di erent types of scheduling problems. They also introduced a reduction digraph that re ected the degree of closeness of similar problem types.…”

Section: Related Researchmentioning

confidence: 99%

Generating interpretable fuzzy rules for adaptive job dispatching

Lee¹,

Yoon²,

Baek³

2001

International Journal of Production Research

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Adaptive scheduling is an approach that selects and applies the most suitable strategy considering the current state of the system. The performance of an adaptive scheduling system relies on the e ectiveness of the mapping knowledge between system states and the best rules in the states. This study proposes a new fuzzy adaptive scheduling method and an automated knowledge acquisition method to acquire and continuously update the required knowledge. In this method, the criteria for scheduling priority are selected to correspond to the performance measures of interest. The decisions are made by rules that re ect those criteria with appropriate weights that are determined according to the system states. A situated rule base for this mapping is built by an automated knowledge acquisition method based on system simulation. D istributed fuzzy sets are used for evaluating the criteria and recognizing the system states. The combined method is distinctive in its similarity to the way human schedulers accumulate and adjust their expertise: qualitatively establishing meaningful criteria and quantitatively optimizing the use of them. As a result, the developed rules may readily be interpreted, adopted and, when necessary, modi ed by human experts. An application of the proposed method to a job-dispatching problem in a hypothetical exible manufacturing system (F M S) shows that the method can develop e ective and robust rules.

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“…These include various local search techniques (Aarts et al 1994), simulated annealing (Matsuo et al 1988), tabu search (Nowicki and Smutnicki 1996), genetic algorithms (Storer et al 1992) and decomposition procedures based on Lagrangian relaxation (Luh and Hoitomt 1993) or work centre-based decompositions (Adams et al 1988, Ovacik and Uzsoy 1997, Pinedo and Singer 1999. Other authors have applied artificial intelligence-based approaches (Fox and Smith 1984, Lamatsch et al 1988, Fox 1990, Kempf et al 1991. Many of these procedures can also be computationally intensive.…”

Section: Introductionmentioning

confidence: 97%

Measures of subproblem criticality in decomposition algorithms for shop scheduling

Aytuğ

Kempf

Uzsoy

2003

International Journal of Production Research

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Work centre-based decomposition approaches, especially variants of the Shifting Bottleneck algorithm, have been very successful in solving job-shop-scheduling problems. These methods decompose the problem into subproblems involving a single work centre (usually a single machine), which they solve sequentially. We propose new measures of subproblem criticality and show via computational experiments that several of these provide solutions comparable in quality with those obtained from previous work in substantially less central processing unit time. IntroductionEffective factory scheduling, which involves the allocation of machines to competing jobs over time, is critical to success in today's highly competitive global industries. While many industrial problems are significantly more complex, the job-shop-scheduling problem has served as a vehicle for many researchers to develop and test new scheduling procedures. In this problem, there are n jobs to be processed on m machines. The routings of the jobs are deterministic and known a priori, as are the processing times of each job on each machine. Each machine can process only one job at a time. We consider here the problems of minimizing makespan (C max ) and maximum lateness (L max ) in this environment. Both these problems, denoted by J//C max and J//L max , respectively, in the notation of Lawler et al. (1993), have been shown to be NP-hard in the strong sense (Garey and Johnson 1979). Hence, some researchers have focused on developing exact procedures based on branch-andbound algorithms (e.g. Carlier and Pinson 1989, Brucker et al. 1994). These methods produce exact solutions, but their worst-case computational burden increases exponentially with the size of the problem instance. In order to be able to apply optimization-based algorithms to industrial problems, the computational time of any algorithm must be short enough that the schedule is generated in a time frame short enough for the resulting schedule to be usable. In semiconductor manufacturing environments where several hundred jobs must be scheduled on several hundred pieces of equipment, this means that algorithms giving high solution quality usually require quite high central processing unit (CPU) times, and hence any reduction in CPU time represents a significant advantage in terms of the practical applicability of the algorithm. A reduction of the order of 10-15% may well represent an absolute

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Schedule-an expert-like system for machine scheduling

Cited by 16 publications

References 3 publications

A review and classification of computer-based manufacturing scheduling tools

A review and classification of computer-based manufacturing scheduling tools

Generating interpretable fuzzy rules for adaptive job dispatching

Measures of subproblem criticality in decomposition algorithms for shop scheduling

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