@conference {Biallaten2020, title = {Truss Optimization using the Simulated Annealing Algorithm}, booktitle = {ACM International Conference Proceeding Series}, year = {2020}, note = {cited By 0}, abstract = {This document presents the results of our work aiming to create a tool for generating trusses. The generated structures undergo an optimizing process to be in the best possible form. The automatic generation of the truss structure is done using an algorithm adapted to the type of an initial design domain. Then, the optimization process is launched to resize the generated structure by minimizing the compliance under constant volume constraint. The size optimization is a question of looking for the best distribution of the cross-sections checking the objective of optimization and guaranteeing the stability of the final solution. We chose to implement this optimization using the simulated annealing algorithm. So, we developed a hybrid method based on the simulated annealing algorithm and an algorithm of bars elimination. {\textcopyright} 2020 ACM.}, keywords = {Automatic Generation, Constant volumes, Constrained optimization, Hybrid method, Information systems, Information use, Initial design, Simulated annealing, Simulated annealing algorithms, Size optimization, Truss optimization, Truss structure, Trusses}, doi = {10.1145/3447568.3448534}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103615098\&doi=10.1145\%2f3447568.3448534\&partnerID=40\&md5=2edcc24e3adf365097bd676455eb98f9}, author = {Biallaten, Z. and Chiheb, R. and El Afia, A.} } @conference {ElHaddaoui2018, title = {Toward a sentiment analysis framework for social media}, booktitle = {ACM International Conference Proceeding Series}, year = {2018}, doi = {10.1145/3230905.3230919}, url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053484908\&doi=10.1145\%2f3230905.3230919\&partnerID=40\&md5=c602c6dc79537942d4d5ac0b9e4a0197}, author = {El Haddaoui, B. and Chiheb, R. and Faizi, R. and Afia, A.E.} }