Environment-Adaptive Genetic Algorithm-based Nesting Scheduling for Sheet-Metal Processing

Abstract

Sheet metal processing is a popular machining technique. In sheet metal processing, as many parts as possible are cut from a metal sheet to effectively use the metal without waste. The parts cut from the sheet metal are processed by a specified due-date. To meet the due-date, scheduling is important. The optimizations of the cutting layout and schedule are called nesting and scheduling, respectively. The relation between them sometimes exhibits a trade-off. To enhance the efficiency of the entire manufacturing process, nesting and scheduling should be considered simultaneously. Therefore, in this study, we proposed an environment-adaptive genetic-algorithm-based nesting scheduling method for the simultaneous consideration of two related problems with different optimization targets. We treated the problems as different environments, and the cutting layout and processing order of the parts evolved in each environment using the genetic algorithm.