TY  - JOUR
T1  - Evaluation of Hybrid Monte-Carlo and Genetic Algorithm for Tropical Timber Joint Strength
AU - Yusoff, Marina AU - Othman, Dzul Fazwan AU - Latiman, Amirul Thaqif AU - Hassan, Rohana 
JO  - Journal of Engineering and Applied Sciences
VL  - 11
IS  - 7
SP  - 1682
EP  - 1686
PY  - 2016
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2016.1682.1686
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2016.1682.1686
KW  - Genetic algorithm
KW  -hybrid genetic algorithm Monte-Carlo
KW  -tensile test
KW  -timber joint
KW  -tropical timber
AB  - The timber strength is one of the prime important aspects of timber structure design. A lot of laboratory experiments have been conducted to determine an appropriate load for timber strength. This paper addresses a new design of a hybrid genetic algorithm-Monte Carlo for load prediction in timber joint. A hybrid of Genetic Algorithm Monte-Carlo is employed to determine the best load value for the prediction of timber joint strength. This study discusses the initial solution to overcome the time consuming and costly incurred of the laboratory experiments. A new solution representation of Genetic Algorithm was addressed with the introduction of Monte-Carlo calculation. Two types of tropical timbers which are Keruing and Sesenduk are used. The results demonstrate faster solution due to fast convergence of obtaining a feasible solution. At the same time the hybrid solution also gives a sub-optimal solution. However, more computational experiments are expected to be done for various types of timbers. The comparison with other computational methods and different parameters should be considered to find better solutions.
ER  -