An iteratively doubling local search for the two-dimensional irregular bin packing problem with limited rotations

Abstract

This paper proposes an iteratively doubling local search approach for the two-dimensional irregular bin packing problem (2DIRBPP) with limited rotations, whose objective is to pack a given set of irregular pieces into the minimum number of rectangular bins. The allowable angles of each piece are limited. To solve this problem, a waste least first decreasing strategy is introduced to assign the piece to the bins. A simple greedy local search approach by moving the pieces from one bin to another is utilized to improve the solution. We adapt an overlap minimization approach to solving the one bin placement problem. The classical bottom-left method is utilized to generate the initial position for each piece, and the random local search by exchanging the positions of two pieces is used to minimize the overlap. Moreover, a novel warm start and an iteratively doubling search strategy are proposed to speed up the search process. The standard benchmark results show that our approach improves the results for most of the instances in the literature.