Flexible jobshop scheduling problem with resource recovery constraints.
Objectives and methods of study: The general objective of this research is to study a scheduling problem found in a local brewery. The main problem can be seen as a parallel machine batch scheduling problem with sequence-dependent setup times, resource constraints, precedence relationships, and capa...
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| Formato: | Tesis |
| Lenguaje: | inglés |
| Publicado: |
2017
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| Acceso en línea: | http://eprints.uanl.mx/14088/1/1080242220.pdf |
| _version_ | 1824413903471247360 |
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| author | Vallikavungal Devassia, Jobish |
| author_facet | Vallikavungal Devassia, Jobish |
| author_sort | Vallikavungal Devassia, Jobish |
| collection | Repositorio Institucional |
| description | Objectives and methods of study: The general objective of this research is to study a scheduling problem found in a local brewery. The main problem can be seen as a parallel machine batch scheduling problem with sequence-dependent setup times, resource constraints, precedence relationships, and capacity constraints.
In the first part of this research, the problem is characterized as a Flexible Job-shop Scheduling Problem with Resource Recovery Constraints. A mixed integer linear formulation is proposed and a large set of instances adapted from the literatura of the Flexible Job-shop Scheduling Problem is used to validate the model. A solution procedure based on a General Variable Neighborhood Search metaheuristic is proposed, the performance of the procedure is evaluated by using a set of instances adapted from the literature.
In the second part, the real problem is addressed. All the assumptions and constraints faced by the decision maker in the brewery are taken into account. Due to the complexity of the problem, no mathematical formulation is presented, instead, a solution method based on a Greedy Randomize Adaptive Search Procedure is proposed. Several real instances are solved by this algorithm and a comparison is carried out between the solutions reported by our GRASP and the ones found through the procedure followed by the decision maker. The computational results reveal the efficiency of our method, considering both the processing time and the completion time of the scheduling. Our algorithm requires less time to generate the production scheduling (few seconds) while the decision maker takes a full day to do it. Moreover, the completion time of the production scheduling generated by our algorithm is shorter than the one generated through the process followed by the decision maker. This time saving leads to an increase of the production capacity of the company.
Contributions: The main contributions of this thesis can be summarized as follows: i) the introduction of a variant of the Flexible Job-shop Scheduling Problem, named as the Flexible Job-shop Scheduling Problem with Resource Recovery Constraints (FRRC); ii) a mixed integer linear formulation and a General Variable Neighborhood Search for the FRRC; and iii) a case study for which a Greedy Randomize Adaptive Search Procedure has been proposed and tested on real and
artificial instances.
The main scientific products generated by this research are: i) an article already published: Sáenz-Alanís, César A., V. D. Jobish, M. Angélica Salazar-Aguilar, and Vincent Boyer. “A parallel machine batch scheduling problem in a brewing company”. The International Journal of Advanced Manufacturing Technology 87, no. 1-4 (2016): 65-75. ii) another article submitted to the International Journal of Production Research for its possible publication; and iii) Scientific presentations and seminars. |
| format | Tesis |
| id | eprints-14088 |
| institution | UANL |
| language | English |
| publishDate | 2017 |
| record_format | eprints |
| spelling | eprints-140882018-06-27T19:59:34Z http://eprints.uanl.mx/14088/ Flexible jobshop scheduling problem with resource recovery constraints. Vallikavungal Devassia, Jobish Objectives and methods of study: The general objective of this research is to study a scheduling problem found in a local brewery. The main problem can be seen as a parallel machine batch scheduling problem with sequence-dependent setup times, resource constraints, precedence relationships, and capacity constraints. In the first part of this research, the problem is characterized as a Flexible Job-shop Scheduling Problem with Resource Recovery Constraints. A mixed integer linear formulation is proposed and a large set of instances adapted from the literatura of the Flexible Job-shop Scheduling Problem is used to validate the model. A solution procedure based on a General Variable Neighborhood Search metaheuristic is proposed, the performance of the procedure is evaluated by using a set of instances adapted from the literature. In the second part, the real problem is addressed. All the assumptions and constraints faced by the decision maker in the brewery are taken into account. Due to the complexity of the problem, no mathematical formulation is presented, instead, a solution method based on a Greedy Randomize Adaptive Search Procedure is proposed. Several real instances are solved by this algorithm and a comparison is carried out between the solutions reported by our GRASP and the ones found through the procedure followed by the decision maker. The computational results reveal the efficiency of our method, considering both the processing time and the completion time of the scheduling. Our algorithm requires less time to generate the production scheduling (few seconds) while the decision maker takes a full day to do it. Moreover, the completion time of the production scheduling generated by our algorithm is shorter than the one generated through the process followed by the decision maker. This time saving leads to an increase of the production capacity of the company. Contributions: The main contributions of this thesis can be summarized as follows: i) the introduction of a variant of the Flexible Job-shop Scheduling Problem, named as the Flexible Job-shop Scheduling Problem with Resource Recovery Constraints (FRRC); ii) a mixed integer linear formulation and a General Variable Neighborhood Search for the FRRC; and iii) a case study for which a Greedy Randomize Adaptive Search Procedure has been proposed and tested on real and artificial instances. The main scientific products generated by this research are: i) an article already published: Sáenz-Alanís, César A., V. D. Jobish, M. Angélica Salazar-Aguilar, and Vincent Boyer. “A parallel machine batch scheduling problem in a brewing company”. The International Journal of Advanced Manufacturing Technology 87, no. 1-4 (2016): 65-75. ii) another article submitted to the International Journal of Production Research for its possible publication; and iii) Scientific presentations and seminars. 2017 Tesis NonPeerReviewed text en cc_by_nc_nd http://eprints.uanl.mx/14088/1/1080242220.pdf http://eprints.uanl.mx/14088/1.haspreviewThumbnailVersion/1080242220.pdf Vallikavungal Devassia, Jobish (2017) Flexible jobshop scheduling problem with resource recovery constraints. Doctorado thesis, Universidad Autónoma de Nuevo León. |
| spellingShingle | Vallikavungal Devassia, Jobish Flexible jobshop scheduling problem with resource recovery constraints. |
| thumbnail | https://rediab.uanl.mx/themes/sandal5/images/online.png |
| title | Flexible jobshop scheduling problem with resource recovery constraints. |
| title_full | Flexible jobshop scheduling problem with resource recovery constraints. |
| title_fullStr | Flexible jobshop scheduling problem with resource recovery constraints. |
| title_full_unstemmed | Flexible jobshop scheduling problem with resource recovery constraints. |
| title_short | Flexible jobshop scheduling problem with resource recovery constraints. |
| title_sort | flexible jobshop scheduling problem with resource recovery constraints |
| url | http://eprints.uanl.mx/14088/1/1080242220.pdf |
| work_keys_str_mv | AT vallikavungaldevassiajobish flexiblejobshopschedulingproblemwithresourcerecoveryconstraints |