- Volume 18 Issue 2
The purpose of this study is to develop a nesting algorithm, using a genetic algorithm to optimize nesting order, and modified No Fit Polygon(NFP) methodology to place parts with the order generated from the previous genetic algorithm. Various genetic algorithm techniques, which have thus far been applied to the Travelling Salesman Problem, were tested. The partially mapped crossover method, the inversion method for mutation, the elitist strategy, and the linear scaling method of fitness value were selected to optimize the nesting order. A modified NFP methodology, with improved searching capability for non-convex polygon, was applied repeatedly to the placement of parts according to the order generated from previous genetic algorithm. Modified NFP, combined with the genetic algorithms that have been proven in TSP, were applied to the nesting problem. For two example cases, the combined nesting algorithm, proposed in this study, shows better results than that from previous studies.
- 한국 CAD/CAM 학회논문집 2차원 공간에서의 휴리스틱 배치 알고리즘 및 구현에 관한 연구 임성국;양성모;고석호;김현정;한관희
- IEEE Trans. Syst. Man and Cyber. v.SMC-6 no.4 A Solution of the Rectangular Cutting Stock Problem Adamowicz,M.;Albano,A.
- Roport, European Business Management School Singleton A New Procedure for Derving the No-Fit Polygon Bennell J.A.;Dowsland K.A.;Dowsland W.B.
- Handbook of Genetic Algorithms Davis L.
- Evolutionary Computation v.3 no.3 Soving Pattern Nesting Problems with Genetic Algorithms Employing Task Decomposition and Contact Detection Dighe,R.;Jakiela,M.J.
- ASME, Advances in Design Automation v.1 no.65-1 Hybrid Approach for Optimal Nesting using a Genetic Algorithm and a Local Minimization Algorithm Fujita,K.;Akagi,S.;Hirokawa,N.
- European Journal of Operation Research v.84 A New Algorithm for the Minimal-Area Convex Enclosure Problem Grinde,R.B.;Cavalier,T.M.
- Journal of the Society of Naval Architects of Japan v.178 Automatic Nesting System by Use of Genetic Algorithm Yamauchi,S.;Tezuka K.