Tong, T K L and Tam, C M (2003) Fuzzy optimisation of labour allocation by genetic algorithms. Engineering, Construction and Architectural Management, 10(2), pp. 146-155. ISSN 0969-9988
Abstract
Multi-skilled labour allocation in a defined time frame falls into the class of non-polynomial (NP) hard problems, solutions to which can only be obtained through repeated trials and errors. The application of fuzzy genetic algorithms (GA) optimisation model provides an efficient way to arrive at a "near-optimal" solution. In this paper, a fuzzy GA optimisation model of labour allocation is presented to illustrate how the near optimal solution can be obtained.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | allocation models; fuzzy sets; genetic algorithms; labour force; multi-skilling |
| Index terms: | fuzzy optimization, genetic algorithm, labour force, skilled labour, multi-skilling, fuzzy set, falls |
| Subjects: | algorithms, health risk and incident analysis, economics, management, flexibility, decision-making and optimization |
| Topics: | Supply Chain Management, Health and Safety, Human Resources, Research Practice, Digital Applications |
| Descriptive scope: | 2 PC |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here