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Vol. 155, Issue 8, August 2013, pp. 232-241




Genetic Algorithm-based Hybrid Methods for a Flexible Single-operation Serial-batch Scheduling Problem with Mold Constraints
Hegen Xiong, Huali Fan, Gongfa Li

School of Machine and Automation of Wuhan University of Science and Technology, No. 947, Heping Road, Qingshan District, Wuhan City, 430081,China
Tel.: +86-15697181033, fax: +86-02768862283
E-mail: xionghegen@126.com


Received: 14 July 2013   /Accepted: 12 August 2013   /Published: 20 August 2013

Digital Sensors and Sensor Sysstems


Abstract: Scheduling in a manufacturing system is currently a research hotspot. This paper proposes a flexible, single-operation, serial-batch scheduling problem with mold constraints that arise from injection molding production. In such a scheduling problem, three decision problems exist: product batch splitting, sequencing, and resource selection. A divide-and-conquer framework is introduced to solve the three decision problems. A hybrid algorithm combining the genetic algorithm for sequencing with the heuristic algorithm for resource selection is developed. We design an experimental case to which the corresponding simulation scheduling process is applied. We present a detailed analysis of the simulation results, which indicate that the solution framework and the hybrid algorithm are effective.


Keywords: Serial-batch scheduling, Mold constraints, Injection molding production, Genetic algorithm, Dispatching rule.


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