Aggregate planning for probabilistic demand with internal and external storage
Aggregate planning for probabilistic demand with internal and external storage
| dc.creator | Biazzi, Jorge Luiz | |
| dc.date | 2018-06-15 | |
| dc.date.accessioned | 2022-11-04T02:55:15Z | |
| dc.date.available | 2022-11-04T02:55:15Z | |
| dc.identifier | https://bibliotecadigital.fgv.br/ojs/index.php/joscm/article/view/69583 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/5072092 | |
| dc.description | This paper presents three approaches to support decision-making for production planning, sales and inventory problems. They work in a situation with: non-stationary probabilistic demand; production capacity in regular hours and overtime; shortage leads to lost sales; limited internal storage space; and ordering costs resulting from machine preparation are negligible. In the first approach, we consider the problem as linear and deterministic. In the second, safety inventories are used to fill a probabilistic demand, but the possibility of stockout is not considered. The third approach estimates shortage resulting from demand uncertainty. The last two approaches use iterative processes to re-estimate unit holding cost, which is the basis to calculate safety inventories in each period of the horizon. Using Microsoft Excel Solver, with linear programming and nonlinear search functions, a hypothetical example (but strongly based on real-life companies) and some scenarios permit concluding that developing more realistic and complex models may not provide significant benefits. | en-US |
| dc.description | This paper presents three approaches to support decision-making for production planning, sales and inventory problems. They work in a situation with: non-stationary probabilistic demand; production capacity in regular hours and overtime; shortage leads to lost sales; limited internal storage space; and ordering costs resulting from machine preparation are negligible. In the first approach, we consider the problem as linear and deterministic. In the second, safety inventories are used to fill a probabilistic demand, but the possibility of stockout is not considered. The third approach estimates shortage resulting from demand uncertainty. The last two approaches use iterative processes to re-estimate unit holding cost, which is the basis to calculate safety inventories in each period of the horizon. Using Microsoft Excel Solver, with linear programming and nonlinear search functions, a hypothetical example (but strongly based on real-life companies) permits concluding that developing more realistic and complex models may not provide significant benefits. | pt-BR |
| dc.format | application/pdf | |
| dc.language | eng | |
| dc.publisher | FGV EAESP | en-US |
| dc.relation | https://bibliotecadigital.fgv.br/ojs/index.php/joscm/article/view/69583/pdf_50 | |
| dc.rights | Copyright (c) 2018 Journal of Operations and Supply Chain Management | pt-BR |
| dc.source | Journal of Operations and Supply Chain Management; Vol. 11 No. 1 (2018): January - June; 37-52 | en-US |
| dc.source | Journal of Operations and Supply Chain Management; v. 11 n. 1 (2018): January - June; 37-52 | pt-BR |
| dc.source | 1984-3046 | |
| dc.subject | Inventory | en-US |
| dc.subject | non-stationary probabilistic demand | en-US |
| dc.subject | aggregate production planning | en-US |
| dc.subject | sales and operations mathematical models | en-US |
| dc.subject | no ordering costs | en-US |
| dc.subject | Inventory | pt-BR |
| dc.subject | non-stationary probabilistic demand | pt-BR |
| dc.subject | aggregate production planning | pt-BR |
| dc.title | Aggregate planning for probabilistic demand with internal and external storage | en-US |
| dc.title | Aggregate planning for probabilistic demand with internal and external storage | pt-BR |
| dc.type | info:eu-repo/semantics/article | |
| dc.type | info:eu-repo/semantics/publishedVersion |