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

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.

• Publication year

  2013

• Venue

  TheScientificWorldJournal

• Publication date

  2013-12-24

• Fields of study

  Medicine, Computer Science, Engineering

• Identifiers
  DOI 10.1155/2013/202683PMID 24489491PMCID 3886606
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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