A New PSO-based Algorithm for Two-Dimensional Non-Guillotine Non-Oriented Cutting Stock Problem
In this paper, a new algorithm is proposed for the two-dimensional non-guillotine non-oriented cutting stock problem. The considered problem consists of cutting small rectangular pieces of predetermined sizes from large but finite rectangular plates. The objective is to generate cutting patterns tha...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2017-04-01
|
| Series: | Applied Artificial Intelligence |
| Online Access: | http://dx.doi.org/10.1080/08839514.2017.1346966 |
| Summary: | In this paper, a new algorithm is proposed for the two-dimensional non-guillotine non-oriented cutting stock problem. The considered problem consists of cutting small rectangular pieces of predetermined sizes from large but finite rectangular plates. The objective is to generate cutting patterns that minimize the unused area and fulfill customer orders. The proposed algorithm is a combination of a new particle swarm optimization approach with a heuristic criterion inspired from the literature. The algorithm is tested on twenty-two instances divided into two sets. Corresponding results show the algorithm efficiency in optimizing the trim loss that is comprised between 2.6% and 7.8% for all considered instances. |
|---|---|
| ISSN: | 0883-9514 1087-6545 |