Determining the most appropriate set of weekly working hours for planning annualised working time
Annualised hours—the irregular distribution of working hours over a year—allow companies to adapt capacity to demand, thus reducing overtime, the number of temporary workers and inventory costs. To avoid a significant deterioration in working conditions, many laws and agreements constrain the distri...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2008 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/6096 |
| Acceso en línea: | https://hdl.handle.net/2117/6096 |
| Access Level: | acceso abierto |
| Palabra clave: | Manpower planning Human resources Annualised hours Aggregated planning Recursos humanos Recursos humans Planificación de la mano de obra Planificació de la mà d'obra Horas de trabajo anual Hores de treball anual Planificación agregada Planificació agregada Producció -- Planificació Àrees temàtiques de la UPC::Economia i organització d'empreses::Direcció d'operacions |
| Sumario: | Annualised hours—the irregular distribution of working hours over a year—allow companies to adapt capacity to demand, thus reducing overtime, the number of temporary workers and inventory costs. To avoid a significant deterioration in working conditions, many laws and agreements constrain the distribution of working time. One way of doing this is by specifying a finite set of weekly working hours and bounding the annual number of weeks of each type. Although this set has a great impact on the solution, it is usually agreed without taking all the available data (demand, costs, etc.) into consideration. This paper proposes a method for selecting the most appropriate set of weekly working hours and establishing an annual plan or working time for each worker as a way of optimising service level. To this end, two mathematical programming models are proposed. By means of a computational experiment, it is shown that one of the models can be solved in short computing times and can thus be used as a decision-making tool. |
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