Solution approaches for a real-life resource-constrained parallel machine scheduling problem

Edis, Emrah B.; Özkarahan, İrem

doi:10.1007/s00170-011-3454-8

Cited by 35 publications

(21 citation statements)

References 33 publications

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“…Moreover, among the studies with computational experiments, the majority of papers, excluding a few ones (Blazewicz et al, 1993;Li et al, 2003;Ventura and Kim, 2003;Edis and Ozkarahan, 2012), deal with small (e.g., 10-15 jobs, 3-5 machines) or medium (e.g., 30-50 jobs, 5-10 machines) size problems.…”

Section: Other Important Issuesmentioning

confidence: 98%

“…With the combined IP/CP model, they reach optimal results for instances with up to 50 jobs and five machines in less than 1 hour of computation time. Later, for a similar problem, Edis and Ozkarahan (2012) develop IP/IP and IP/CP sequential heuristic approaches where the job-machine assignment is made with an IP loading model and scheduling of the jobs on dedicated machines is obtained by an IP (and alternatively CP) scheduling model. They show that the IP scheduling model performs better when the additional resource constraints are loose, while the CP scheduling model gives better results when the additional resource constraints are tight.…”

Section: Approximation Algorithms With Worst-case Boundsmentioning

confidence: 99%

“…In case of machine eligibility restrictions, job i is allowed to be processed only on a subset M i of m machines. Edis et al (2008) and Edis and Ozkarahan (2012) consider machine eligibility restrictions for the RCPMSPs with unit and arbitrary processing times, respectively. Machine eligibility restrictions are also considered in a related field, that is, PMS with auxiliary equipment of constraints (Tamaki et al, 1993;Chen, 2005;Chen and Wu, 2006).…”

Section: Machine Environmentmentioning

confidence: 99%

See 2 more Smart Citations

Parallel machine scheduling with additional resources: Notation, classification, models and solution methods

Edis

Oğuz

Özkarahan

2013

European Journal of Operational Research

Self Cite

133

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Section: Other Important Issuesmentioning

confidence: 98%

Section: Approximation Algorithms With Worst-case Boundsmentioning

confidence: 99%

Section: Machine Environmentmentioning

confidence: 99%

See 1 more Smart Citation

Parallel machine scheduling with additional resources: Notation, classification, models and solution methods

Edis

Oğuz

Özkarahan

2013

European Journal of Operational Research

Self Cite

133

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“…Studies on parallel machine scheduling can be categorized into three types: identical, uniform and unrelated parallel machine scheduling problems (Cheng & Sin, 1990). Among these categories, the parallel unrelated machine problems have been much less studied (Edis & Ozkarahan, 2012). In addition, sequence-dependent processing times between jobs have not been taken into account until recently (Vallada & Ruiz, 2011;Sereshti & Bijari, 2013).…”

Section: Scheduling Problemmentioning

confidence: 99%

Improving effectiveness of parallel machine scheduling with earliness and tardiness costs: A case study

Muñoz-Villamizar¹,

Santos²,

Montoya‐Torres³

et al. 2019

10.5267/j.ijiec

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This paper assesses the effectiveness in scheduling independent jobs with earliness/tardiness costs and variable setup times applying the Overall Equipment Effectiveness (OEE). The OEE is a common metric for measuring the manufacturing productivity. We defined a mixed-integer linear programming formulation of the parallel machine scheduling problem with four different objective functions in order to compare different scheduling configurations. Real data, from a plastic container manufacturing company located in the Basque Country (Spain), were used to validate this approach. A sensitivity analysis was performed with different production capacities and earliness/tardiness costs in order to evaluate the trade-offs between economic performance (i.e., costs) and the partial rates of OEE (i.e., quality, performance and availability). The objective of this study is to propose a guideline to help management make decisions regarding the measurement and improvement of scheduling effectiveness through contemplating earliness, tardiness and variable setup times.

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“…As indicated above, none of these researchers taken into account the resource constraints. Only Edis and Ozkarahan (2012) considered machine eligibility and resource constraints for identical PMSP simultaneously, however, they did not propose any meta-heuristic algorithm for this problem. To the best of our knowledge, this research is the first to propose a meta-heuristic algorithm for the mentioned problem.…”

Section: Introductionmentioning

confidence: 98%

Design of an efficient genetic algorithm for resource-constrained unrelated parallel machine scheduling problem with machine eligibility restrictions

Afzalirad

Shafipour

2015

J Intell Manuf

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This study addresses a resource-constrained unrelated parallel machine scheduling problem with machine eligibility restrictions. Majority of the traditional scheduling problems in parallel machine environment deal with machine as the only resource. However, other resources such as labors, tools, jigs, fixtures, pallets, dies, and industrial robots are not only required for processing jobs but also are often restricted. Considering other resources makes the scheduling problems more realistic and practical to implement in manufacturing environments. First, an integer mathematical programming model with the objective of minimizing makespan is developed for this problem. Noteworthy, due to NP-hardness of the considered problem, application of meta-heuristic is avoidable. Furthermore, two new genetic algorithms including a pure genetic algorithm and a genetic algorithm along with a heuristic procedure are proposed to tackle this problem. With regard to the fact that appropriate design of the parameters has a significant effect on the performance of algorithms, hence, we calibrate the parameters of these algorithms by using the response surface method. The performance of the proposed algorithms is evaluated by a number of numerical examples. The computational results demonstrated that the proposed genetic algorithm is an effective and appropriate approach for our investigated problem.

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Solution approaches for a real-life resource-constrained parallel machine scheduling problem

Cited by 35 publications

References 33 publications

Parallel machine scheduling with additional resources: Notation, classification, models and solution methods

Parallel machine scheduling with additional resources: Notation, classification, models and solution methods

Improving effectiveness of parallel machine scheduling with earliness and tardiness costs: A case study

Design of an efficient genetic algorithm for resource-constrained unrelated parallel machine scheduling problem with machine eligibility restrictions

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