Abstract
This work aims to propose a binary version of a new metaheuristic in order to solve the two-dimensional bin packing problem (2D-BPP) which is a NP-hard optimization problem in a strong sense. Various metaheuristics are dedicated to solve 2D-BPP, however, the swarm intelligence algorithms are rarely frequent in this problem. A new algorithm based on the principles of swarm intelligence was recently introduced, called crow search algorithm (CSA), which has been successfully applied to continuous optimization problems. In this paper, the CSA is binarized by applying a sigmoid transformation so as to adapt it for solving the 2D-BPP. An evaluation of the performance of the proposed binary CSA is carried out by standard instances of 2D-BPP, and the experimental results are compared with two state-of-the-art algorithms that are particle swarm optimization algorithm and the well-known heuristic Finite First Fit. The results obtained by the proposed algorithm prove its effectiveness in terms of solution quality and computational time. Until recently, no study exists that deals with CSA algorithm for solving the packing problems in general and 2D-BPP in particular.
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