Ant colony optimization (ACO) algorithms have been widely adopted in solving combinatorial problems, like the traveling salesman problem (TSP). Nevertheless, with a proper transformation to TSP, ACO is capable of solving undirected rural postman problems (URPP) as well. In fact, nozzle path planning problems in 3D printing can be represented as URPP. Therefore, in this work, ACO is utilized as a URPP solver to accelerate the printing process in fused deposition modeling applications. Furthermore, mechanisms which exploit unique properties in 3D models are proposed to further extend the ACO in the above optimization process. These mechanisms are capable of accelerating ACO by adaptively adjusting its number of iterations on-the-fly. Simulation results using real-life 3D models show that the proposed extensions can accelerate ACO without affecting the quality of its solutions significantly.
|Title of host publication||2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Proceedings|
|Publisher||IEEE, Institute of Electrical and Electronics Engineers|
|Publication status||Published - 26 Apr 2018|
|Event||2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018 - Firenze Fiera Congress and Exhibition Center, Florence, Italy|
Duration: 27 May 2018 → 30 May 2018
|Conference||2018 IEEE International Symposium on Circuits and Systems, ISCAS 2018|
|Period||27/05/18 → 30/05/18|