Thesis (MSc (Forest and Wood Science))--University of Stellenbosch, 2011. / ENGLISH ABSTRACT: The percentage yield of sawn timber recovered from logs has a large influence on the profitability of a sawmill. The positioning of the log as it is fed into the primary breakdown saw is one of the factors that impacts on the volume recovery percentage. The log’s position can be adjusted by changes in rotation, offset and skewness and depending on the ranges and increments used for these variables, the number of possible combinations can become substantial. In a sawmill the time available to assess possible log positions is limited and different strategies can be followed to arrive at an optimal or close‐to‐optimal positioning solution without an exhaustive evaluation of solutions. Meta‐heuristics are sometimes used to arrive at solutions for combinatorial optimisation problems in a limited time. The effectiveness of this approach on the optimisation of timber volume recovery based on log form is evaluated in this study using sawmill simulation data of sixty SA pine logs. A new meta‐heuristic, for convenience named the Tentacle algorithm, was developed specifically for the problem of log positioning optimisation. The results obtained with the Tentacle algorithm was compared with results from three existing meta‐heuristics i.e. the Simulated Annealing algorithm, the Population Based Incremental Learning algorithm and the Particle Swarm Optimisation algorithm, in terms of its efficiency and effectiveness in finding good log positioning solutions in a limited time. A fifth method, that of exhaustively searching smaller, high quality areas around the centered and “horns‐up” and “horns‐down” positions in the search space was compared to that of using the meta‐heuristic algorithms. In terms of volume recovery, the Tentacle algorithm performed, on average, the best of the four algorithms evaluated. However, exhaustive searches in the smaller, high quality areas in the search space, outperformed the algorithms. / AFRIKAANSE OPSOMMING: Die herwinningspersentasie van gesaagde planke uit saagblokke het ‘n groot invloed op die winsgewendheid van ‘n saagmeul. Die posisionering van die blok in die primêre saag is een van die faktore wat die herwinningspersentasie beïnvloed. Die blok se posisie kan verstel word deur veranderinge in rotasie, oplyning en skeefheid. Afhangend van die veld ‐en inkrementgrootte kan die hoeveelheid moontlike kombinasies beduidend wees. In ‘n tipiese saagmeul is die beskikbare tyd om moontlike posisies te evalueer beperk en verskeie strategieë kan gevolg word om optimale of nabyoptimale kombinasies te bereik sonder om alle moontlike kombinasies te evalueer. Meta‐heuristieke word soms gebruik om in ‘n beperkte tyd oplossings te vind vir kombinatoriese optimeringsprobleme. Die doeltreffendheid van hierdie metode by die optimering van herwinningspersentasie gebaseer op blokvorm is in hierdie studie ondersoek. Dit is met behulp van saagmeulsimulasiedata soos van sestig SA dennehoutblokke verkry, uitgevoer. ‘n Nuwe meta‐heuristiek, genaamd die Tentakelalgoritme, is tydens hierdie studie spesifiek vir die probleem van blokposisie‐optimering ontwikkel. Die resultate verkry met die Tentakelalgoritme is vergelyk met drie bestaande meta‐heuristieke, nl. die “Simulated Annealing”‐algoritme, die “Population Based Incremental Learning”‐algoritme en die “Particle Swarm Optimisation”‐algoritme in terme van doeltreffendheid om goeie blokposisies in ‘n beperkte tyd te vind. ‘n Vyfde metode, die gebruik van ‘n volledige ondersoek van verkleinde versamelings, rondom hoë‐kwaliteit areas in die soekarea, is vergelyk met die gebruik van die meta‐heuristieke. Hierdie hoë‐kwaliteit areas word gevind rondom die gesentreerde “horns‐up” en “horns‐down” posisies. Die Tentakelalgoritme het gemiddelde die beste herwinningsresultate van die vier meta‐heuristieke wat ondersoek was gelewer. Die volledige ondersoek van verkleinde versamelings in die hoë kwaliteit areas het egter die meta‐heuristieke oortref.