An improved lowest-level best-fit algorithm with memory for the 2D rectangular packing problem

In this paper, a new heuristic algorithm for the two-dimensional rectangular packing problem (2drpp), the Improved Lowest-level Best-Fit with Memory (ILBFM) algorithm, is presented. Three new heuristic rules (ILBF) which belong to the class of packing procedure that preserve lowest-level best-fit first, is proposed. By combining the ILBF heuristic rule with Particle Swarm Optimization (PSO) algorithm, the local best packing sequence is remembered, and retained in the next generation of the particle swarm. In our study, we compare this hybrid algorithm in terms of solution quality on a number of packing problems of different size with some other classical algorithms. The result of experiments shows that the ILBFM algorithm can solve the 2drpp more effectively.