Iterated Local Search Algorithm for the Constrained Two-Dimensional Non-Guillotine Cutting Problem
Abstract
An Iterated Local Search method for the constrained two-dimensional non-guillotine cutting problem is presented. This problem consists in cutting pieces from a large stock rectangle to maximize the total value of pieces cut. In this problem, we take into account restrictions on the number of pieces of each size required to be cut. It can be classified as 2D-SLOPP (two dimensional single large objects placement problem) and has many industrial applications like in wood and steel industries. The proposed Iterated Local Search algorithm in which we use a constructive heuristic and a local search move based on reducing pieces. The algorithm is tested on well known instances from the literature. Our computational results are very competitive compared to the best known solutions of literature and improve a part of them.