Using the population-based incremental learning algorithm with computer simulation : some applications

Bekker, J. ; Olivier, Y. (2008)

CITATION: Bekker, J. & Olivier, Y. 2008. Using the population-based incremental learning algorithm with computer simulation : some applications. South African Journal of Industrial Engineering, 19(1): 53-71, doi: http://dx.doi.org/10.7166/19-1-106.

The original publication is available at http://sajie.journals.ac.za

Article

ENGLISH ABSTRACT: The integration of the population-based incremental learning (PBIL) algorithm with computer simulation shows how this particular combination can be applied to find good solutions to combinatorial optimisation problems. Two illustrative examples are used: the classical inventory problem of finding a reorder point and reorder quantity that minimises costs while achieving a required service level (a stochastic problem); and the signal timing of a complex traffic intersection. Any traffic control system must be designed to minimise the duration of interruptions at intersections while maximising traffic throughput. The duration of the phases of traffic lights is of primary importance in this regard.

AFRIKAANSE OPSOMMING: Die integrasie van die population-based incremental learning (PBIL) algoritme met rekenaarsimulasie word bespreek, en daar word getoon hoe hierdie spesifieke kombinasie aangewend kan word om goeie oplossings vir kombinatoriese optimeringsprobleme te vind. Twee voorbeelde dien as illustrasie: die klassieke voorraadprobleem waarin ’n herbestelvlak en herbestelhoeveelheid bepaal moet word om koste te minimeer maar nogtans ’n vasgestelde diensvlak te handhaaf (’n stochastiese probleem); en die bepaling van die seintye van ’n komplekse verkeerskruising. Enige verkeerbeheerstelsel moet ontwerp word om die duur van die vloeionderbrekings by verkeerskruisings te minimeer en verkeerdeurset te maksimeer. Die tydsduur van die fases van verkeersligte is dus baie belangrik.

Please refer to this item in SUNScholar by using the following persistent URL: http://hdl.handle.net/10019.1/70788
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