Integrated process planning and scheduling in a supply chain

Moon, Chiung; Lee, Young Hae; Jeong, Chan Seok; Yun, YoungSu

doi:10.1016/j.cie.2007.06.018

Cited by 89 publications

(50 citation statements)

References 14 publications

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“…Same problem was also attempted by Shao et al [19] using a modified genetic algorithm, a hybrid GA by Amin-Naseri and Afshari [41] and an improved by Lihong and Shengping [35]. The later three studies obtained a makespan value 14 as compared to 16 by Moon et al [40]. The proposed GA approach also found a makespan value of 14 which was better than above mentioned earlier studies.…”

Section: Methodsmentioning

confidence: 63%

“…Each job has 2 to 4 operations. The objective function addressed by Moon et al [40] was minimisation of makespan. Using an evolutionary search approach, Moon et al [40] found the makespan value of 16.…”

Section: Methodsmentioning

confidence: 99%

“…The objective function addressed by Moon et al [40] was minimisation of makespan. Using an evolutionary search approach, Moon et al [40] found the makespan value of 16. Same problem was also attempted by Shao et al [19] using a modified genetic algorithm, a hybrid GA by Amin-Naseri and Afshari [41] and an improved by Lihong and Shengping [35].…”

Section: Methodsmentioning

confidence: 99%

“…Experiment 5 problem is adapted from Moon et al [40]. The problem has 5-jobs to be scheduled on 5-machines.…”

Section: Methodsmentioning

confidence: 99%

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Integrated process planning and scheduling using genetic algorithms

Chaudhry

Usman

2017

Teh. vjesn.

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INTEGRATED PROCESS PLANNING AND SCHEDULING USING GENETIC ALGORITHMS Imran Ali Chaudhry, Muhammad UsmanOriginal scientific paper Process planning and scheduling are two of the most important functions in any manufacturing system. Traditionally process planning and scheduling are considered as two separate functions. In this paper a Genetic Algorithm (GA) for integrated process planning and scheduling is proposed where selection of the best process plan and scheduling of jobs in a job shop environment are done simultaneously. In the proposed approach a domain independent spreadsheet based approach is presented to solve this class of problems. The precedence relations among job operations are considered in the model, based on which implicit representation of a feasible process plans for each job can be done. To verify the performance and feasibility of the presented approach, the proposed algorithm has been evaluated against a number of benchmark problems that have been adapted from the previously published literature. The experimental results show that the proposed approach can efficiently achieve optimal or near-optimal solutions for the problems adopted from literature. It is also demonstrated that the proposed algorithm is of general purpose in application and could be used for the optimisation of any objective function without changing the model or the basic GA routine. Keywords: integrated process planning and scheduling (IPPS); genetic algorithms; job shop Integracija projektiranja tehnoloških procesa i planiranja primjenom genetičkih algoritamaIzvorni znanstveni članak Projektiranje tehnoloških procesa i planiranje predstavljaju dvije najvažnije funkcije svakog proizvodnog procesa. Tradicionalno se one smatraju dvjema odvojenim funkcijama. U ovom se radu predlaže Genetički Algoritam (GA) za integraciju ovih aktivnosti, gdje se simultano odvija izbor najboljeg tehnološkog procesa i vremenski plan poslova u pogonu. U radu se za rješavanje te vrste problema predstavlja pristup zasnovan na proračunskoj tablici neovisnog područja. U modelu se razmatraju odnosi prvenstva u izvođenju poslova na temelju kojih se donosi implicitno predstavljanje mogućih planova za izvršenje svakog posla. Zbog provjere izvršenja i ostvarivosti predstavljenog pristupa, predloženi se algoritam provjeravao na nizu referentnih problema prilagođenih iz ranije objavljene literature. Eksperimentalni rezultati pokazuju da se predloženim pristupom mogu učinkoviti postići optimalna ili njima blizu rješenja za probleme prilagođene iz literature. Također je pokazano da predloženi algoritam ima opću namjenu i može se primijeniti za optimizaciju bilo koje objektivne funkcije bez promjene modela ili osnovne GA rutine. Ključne riječi: integracija projektiranja tehnoloških proces i planiranja (IPPS); genetički algoritami; radna mjesta

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Section: Methodsmentioning

confidence: 63%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…Experiment 5 problem is adapted from Moon et al [40]. The problem has 5-jobs to be scheduled on 5-machines.…”

Section: Methodsmentioning

confidence: 99%

See 2 more Smart Citations

Integrated process planning and scheduling using genetic algorithms

Chaudhry

Usman

2017

Teh. vjesn.

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“…Adopted from Moon et al [14] The best solution obtained is 14. The Gantt chart for the best solution is shown in fig.…”

Section: ) Problemmentioning

confidence: 99%

A New Priority-Sort Based Optimization Algorithm for Integrated Process Planning and Scheduling

Aqel¹,

Ausaf²,

Li³

et al. 2013

IJMO

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Abstract-Modern manufacturing systems emphasize the need to improve the overall efficiency of the system and achieve global optimality rather than striving for excellence in isolated individual components. Integration of process planning and scheduling, which were previously treated as spate entities, has become an important area of research for accomplishing this goal. This paper presents a novel optimization algorithm for integrated process planning and scheduling (IPPS) problems. The algorithm is based on sorting the operations into different priorities. The experimental results show that the proposed algorithm can effectively solve IPPS problems.Index Terms-Distributed process planning, Integrated process planning and scheduling, Optimization algorithm, Priority-sort based optimization algorithm.

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References

2011

Scheduling in Supply Chains Using Mixed Integer Programming

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Integrated process planning and scheduling in a supply chain

Cited by 89 publications

References 14 publications

Integrated process planning and scheduling using genetic algorithms

Integrated process planning and scheduling using genetic algorithms

A New Priority-Sort Based Optimization Algorithm for Integrated Process Planning and Scheduling

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