Performance Analysis of Selective Breeding Algorithm on One Dimensional Bin Packing Problems

Abstract

The bin packing optimization problem packs a set of objects into a set of bins so that the amount of wasted space is minimized. The bin packing problem has many important applications. The objective is to find a feasible assignment of all weights to bins that minimizes the total number of bins used. The bin packing problem models several practical problems in such diverse areas as industrial control, computer systems, machine scheduling, VLSI chip layout and etc. Selective breeding algorithm (SBA) is an iterative procedure which borrows the ideas of artificial selection and breeding process. By simulating artificial evolution in this way SBA algorithm can easily solve complex problems. One dimensional bin packing benchmark problems are taken for evaluating the performance of the SBA. The computational results of SBA algorithm show optimal solution for the tested benchmark problems. The proposed SBA algorithm is a good problem-solving technique for one dimensional bin packing problems.