A genetic algorithm approach to bin packing in an ion plating cell

Abstract

A bin packing (BP) problem is an industrial problem that arises when grouping items into appropriate bins to minimize cost and the number of bins used. In this study, the ion plating industry requires a similar approach when allocating production jobs into batches for producing better-quality products and enabling deadlines to be met so that the customer is satisfied. The aim of this paper is to develop a BP model based on genetic algorithms (GAs) to (a) introduce quality of product and service into bin packing problems and (b) improve the production efficiency by reducing the production unit cost in ion plating. A GA is chosen since it is one of the best heuristic algorithms for solving optimization problems. In the case study, industrial data of a precious-metal finishing company have been input into the proposed bin packing genetic algorithm (BPGA) model, and the computational results have been compared with these industrial data. The results demonstrated that less resource would be required by applying the proposed model in solving a BP problem in the ion plating cell.