A mathematical model for optimising the strategic staff planning in universities is used to analyse the impact of different personnel and academic policies on the strategic staff plan, considering a preferable staff composition. The personnel policies are evaluated allowing or not the dismissals of permanent workers; the ratio of internal promotion for workers and the personnel budget. The academic policies are tested through the impact of different demand trends. Addressing the specificities of the university, the optimisation model considers not only economic criteria, i.e., personnel costs, but also other factors related to the fulfilment of the required service level and the achievement of a preferable workforce composition. Several computational scenarios are used, based on real data from the Universitat Politècnica de Catalunya (Barcelona, Spain). The results show the adjustment to the preferable workforce composition through the available mechanisms (dismissals, hiring and internal promotions).
This paper focuses on the integration of marketing and production
decisions regarding aggregate planning in industrial companies. The main
contributions to the literature are described briefly and used to present a
summary of the state of the art. This review will enable the study of the
interrelations between the key variables of marketing decision-making (price
and/or promotion) and production decision-making (product quantity, staff size,
working hours and inventory level) and thereby contribute to the development
of integrated decision models. These contributions are then analysed in relation
to mathematical programming models that include marketing and production
variables in aggregate planning. Finally, future lines of research are proposed.
This paper focuses on production systems that consist of multiple parallel assembly lines. The main literature contributions are briefly described and used to present a summary of the state of the art. The advantages and disadvantages of adopting multiple lines are discussed and the multiple assembly line balancing problem and its relevant characteristics are described.