Authors:
André Kubagawa Sato
;
Thiago de Castro Martins
and
Marcos de Sales Guerra Tsuzuki
Affiliation:
Escola Politécnica da Universidade de São Paulo, Brazil
Keyword(s):
Cutting and packing, Simulated annealing, Placement problems, Optimization, Probabilistic heuristic.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Energy Efficiency and Green Manufacturing
;
Formal Methods
;
Industrial Engineering
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Optimization Algorithms
;
Planning and Scheduling
;
Production Planning, Scheduling and Control
;
Simulation and Modeling
;
Symbolic Systems
Abstract:
The two-dimensional irregular open dimension packing problem is a combinatorial optimization problem that searches a layout for a given set of irregular items within a rectangular container so that no item overlaps with other items or protrudes from the container, where each irregular item is not necessarily convex. The container has a fixed width, while its length can change so that all items are placed in it. The objective is to find a layout of the set of polygons that minimizes the length of the container. The proposed algorithm constructively creates layouts from an ordered list of items and a placement heuristic. The placement determines the collision free region (represents the set of translations to create a feasible layout) for the item to be placed. It is shown that the collision free region must be calculated using non-regularized Boolean operations, as contours of no-fit polygons should be ignored. The proposed algorithm to solve the placement problem has two levels, in t
he internal level the container has fixed dimensions, and the external level reduces or increases the variable dimension. The placement heuristic searches for degenerated vertices and edges as they represent local maximum compaction. Computational comparisons on benchmark problems show that the proposed algorithm generated highly competitive solutions. Moreover, our algorithm updated some best known results.
(More)