Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/155427 
Erscheinungsjahr: 
1994
Schriftenreihe/Nr.: 
Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel No. 356
Verlag: 
Universität Kiel, Institut für Betriebswirtschaftslehre, Kiel
Zusammenfassung: 
Based upon an empirical survey among the 200 biggest CPA firms in Germany an hierarchical modeling framework for audit-staff scheduling with three levels has been developed. For the second level, the so-called medium-to-short-term planning, a binary optimization model is introduced which is closely related to resource-constrained project scheduling. In an extensive computational study several genetic algorithms (GA) with and without domain-specific knowledge as well as a greedy randomized algorithm (RA) are investigated. Besides introducing a generalization concerning the representation of the genes of a GA which is applicable to a wide range of recent procedures it is proved that the RA is a special case of a GA. Furthermore, we observed that a GA of a modest population size with domain-specific knowledge performed best if at least a certain number of individuals is generated.
Schlagwörter: 
Local Search
Genetic Algorithms
Greedy Randomized Algorithms
Regret-Based Biased Random Sampling
Project Management / Scheduling
Audit-Staff Scheduling
Dokumentart: 
Working Paper
Dokumentversion: 
Digitized Version

Datei(en):
Datei
Größe





Publikationen in EconStor sind urheberrechtlich geschützt.