GA and GWO algorithm for the special bin packing problem encountered in field of aircraft arrangement

Abstract

This paper addresses a special case of irregular bin packing problem which the irregular pieces with free rotation have to fill a large irregular stock sheet with defective regions while satisfying the special boundary constraint, i.e., the piece can protrude from the sheet so long as the key points in the piece’s interior lie within the container. The objective of this problem is to maximize the number of filled pieces. To our best knowledge, the piece must be placed completely inside the sheet for all packing problem tackled by published literature. Thus, existing approaches are not good solutions to this special packing problem. To achieve the goal of automated arrangement of pieces and maximize the space utilization, the genetic algorithm and grey wolf optimization algorithm are designed to solve it. The genetic algorithm adopts the elitism strategy for maintaining the portion of the best chromosomes. A new method of updating the main controlling parameter is applied for reinforcing the exploration ability of the grey wolf optimization. These two algorithms use a vector of pieces as the solution representation, and a novel heuristic algorithm decodes it to produce a layout. The proposed heuristic algorithm divides the process of packing into two stages with the objective of satisfying constraints and achieving good space utilization of sheet. Computational experiments show that the presented methods can solve this new kind of the packing problem very well.