A combined integer/constraint programming approach to a resource-constrained parallel machine scheduling problem with machine eligibility restrictions

Edis, Emrah B.; Özkarahan, İrem

doi:10.1080/03052151003759117

Cited by 52 publications

(14 citation statements)

References 37 publications

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“…Edis and Ozkarahan (2011) develop CP and IP/CP combined models for the P|res1Á2, M i |C max problem and achieve improvements in the computational performance particularly with IP/CP combined model. They also analyze the effect of machine flexibility on the proposed models and find out that the combined IP/CP model gives its best performance for the problems with high processing flexibility.…”

Section: Approximation Algorithms With Worst-case Boundsmentioning

confidence: 99%

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

Edis

Oğuz

Özkarahan

2013

European Journal of Operational Research

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133

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Section: Approximation Algorithms With Worst-case Boundsmentioning

confidence: 99%

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

Edis

Oğuz

Özkarahan

2013

European Journal of Operational Research

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133

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“…Some works related to manufacturing systems can be found in Edis and Ozkarahan (2012), Bitar et al (2016) and Ventura and D. (2003). More recently, in Edis and Ozkarahan (2011) and Edis and Oguz (2012), mathematical models for different variations of the problem are proposed. In Edis et al (2013) a classification and a summary of solution methods for parallel machine scheduling problems with additional resources are provided.…”

Section: Literature Reviewmentioning

confidence: 99%

Heuristic algorithms for the unrelated parallel machine scheduling problem with one scarce additional resource

Villa

Vallada

Fanjul-Peyro

2018

Expert Systems with Applications

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Villa Juliá, MF.; Vallada Regalado, E.; Fanjul Peyró, L. (2018). Heuristic algorithms for the unrelated parallel machine scheduling problem with one scarce additional resource. Expert Systems with Applications. 93:28-38. https://doi. AbstractIn this paper, we study the unrelated parallel machine scheduling problem with one scarce additional resource to minimise the maximum completion time of the jobs or makespan. Several heuristics are proposed following two strategies: the first one is based on the consideration of the resource constraint during the whole solution construction process. The second one starts from several assignment rules without considering the resource constraint, and repairs the non feasible assignments in order to obtain a feasible solution. Several computation experiments are carried out over an extensive benchmark. A comparative evaluation against previously proposed mathematical models and matheuristics (combination of mathematical models and heuristics) is carried out. From the results, we can conclude that our methods outperform the existing ones, and the second strategy performs better, especially for large instances.

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“…For some other versions of parallel machine scheduling problems, a double or combined modeling approach is reported to be an efficient solution method. Edis and Ozkarahan (2011) developed a combined CP/MP model formulation which tackles "resource-constrained identical parallel machine scheduling problem with machine eligibility restrictions" and showed that the combined CP/MP model is able to find the optimal solution in most of the test instances with substantial improvements in solution time as opposed to pure ILP and CP models. Similar success of the combined CP/MP approach is reported by Edis and Oguz (2012) who tackled parallel the machine scheduling problem with flexible resources.…”

Section: Problem Modeling: Mathematical Versus Constraint Programmingmentioning

confidence: 99%

Analysis of a parallel machine scheduling problem with sequence dependent setup times and job availability intervals

Gedik

Rainwater

Nachtmann

et al. 2016

European Journal of Operational Research

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In this study, we propose constraint programming (CP) model and logic-based Benders algorithms in order to make the best decisions for scheduling non-identical jobs with availability intervals and sequence dependent setup times on unrelated parallel machines in a fixed planning horizon. In this problem, each job has a profit, cost and must be assigned to at most one machine in such a way that total profit is maximized. In addition, the total cost has to be less than or equal to a budget level. Computational tests are performed on a real-life case study prepared in collaboration with the U.S. Army Corps of Engineers (USACE). Our initial investigations show that the pure CP model is very efficient in obtaining good quality feasible solutions but, fails to report the optimal solution for the majority of the problem instances. On the other hand, the two logic-based Benders decomposition algorithms are able to obtain near optimal solutions for 86 instances out of 90 examinees. For the remaining instances, they provide a feasible solution. Further investigations show the high quality of the solutions obtained by the pure CP model.

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A combined integer/constraint programming approach to a resource-constrained parallel machine scheduling problem with machine eligibility restrictions

Cited by 52 publications

References 37 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

Heuristic algorithms for the unrelated parallel machine scheduling problem with one scarce additional resource

Analysis of a parallel machine scheduling problem with sequence dependent setup times and job availability intervals

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