An Improved Hierarchical Genetic Algorithm for Sheet Cutting Scheduling with Process Constraints. (24th December 2013)

• Record Type: Journal Article
• Authors: Rao, Yunqing; Qi, Dezhong; Li, Jinling
• Other Names: Chen T. Academic Editor.; Cheng Q. Academic Editor.; Yang J. Academic Editor.
• Is Part Of: TheScientificWorldjournal. Volume 2013(2013)
• Publication Date: 2013-12-24
• Subjects: Science -- Periodicals; Technology -- Periodicals; Medicine -- Periodicals; 505
• DOI: 10.1155/2013/202683
• Languages: English
• ISSNs: 2356-6140

Abstract

Abstract : 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.