An Improved Hierarchical Genetic Algorithm for Sheet Cutting Scheduling with Process Constraints

Abstract EN

For the first time, an improved hierarchical genetic algorithm for sheet cutting problem which involves n cutting patterns for m non-identical parallel machines with process constraints has been proposed in the integrated cutting stock model.

The objective of the cutting scheduling problem is minimizing the weighted completed time.

A mathematical model for this problem is presented, an improved hierarchical genetic algorithm (ant colony—hierarchical genetic algorithm) is developed for better solution, and a hierarchical coding method is used based on the characteristics of the problem.

Furthermore, to speed up convergence rates and resolve local convergence issues, a kind of adaptive crossover probability and mutation probability is used in this algorithm.

The computational result and comparison prove that the presented approach is quite effective for the considered problem.