City Research Online

Abstract

This research describes the establishment and optimisation of a stochastic simulation model of an employment system which controls the manpower level in an R & D workforce.

In order to ensure the closed-loop stability of the simulation, the processes within the simulation were represented by approximate deterministic transfer functions. The control parameters of the simulation were then chosen to guarantee stability, even under extreme operating conditions.

Using a suitable objective function, the control parameters of the simulation were varied in order to minimise the objective function. Cost reductions of the order of 30% were achieved.

Attempts to validate the simulation model with respect to the real-world system have not been successful as the available data are insufficient to allow this. Nevertheless, the optimised simulation does exhibit superior performance to that of the real-world system, although this is-partly achieved by sacrificing "social responsibility" in the decision process.

Attempts to validate the control system design model with respect to the stochastic simulation model have achieved only limited success. The simulation is more stable than the design theory would suggest. Simple rules for the guidance of personnel department activity have been devised.

A simulation "language" was specially developed for this research, as existing languages were either not available or not appropriate.

Publication Type:	Thesis (Doctoral)
Subjects:	H Social Sciences > HA Statistics H Social Sciences > HB Economic Theory H Social Sciences > HD Industries. Land use. Labor H Social Sciences > HD Industries. Land use. Labor > HD28 Management. Industrial Management
Departments:	Bayes Business School > Bayes Business School Doctoral Theses Bayes Business School > Faculty of Management Doctoral Theses

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