SOLVING A HYBRID JOB-SHOP SCHEDULING PROBLEM WITH SPACE CONSTRAINTS AND REENTRANT PROCESS BY A GENETIC ALGORITHM: A CASE STUDY
DOI:
https://doi.org/10.23055/ijietap.2017.24.5.2371Keywords:
scheduling, optimization, genetic algorithm, flexible job shop, hybrid job shop, pipe spoolAbstract
In this paper, several concepts and techniques of job-shop scheduling are adjusted and applied to the real-life scheduling problem at a pipe spool fabrication shop. A genetic algorithm (GA) is developed to create a feasible and active schedule for the operational level of pipe spool fabrication with the aims of minimizing completion time of all spools, i.e. makespan. In the proposed algorithm, an enhanced solution coding is used to represent a schedule for the fabrication shop. To generate high quality initial population, we designed an Operation order-based Global Selection (OGS). This operator is taken into account both the operation processing times and workload of machines while it is assigning machines to the operations The precedence preserving order-based crossover (POX) and uniform crossover are used appropriately, and an intelligent mutation operator is carried out in reproduction phase. The proposed algorithm is applied on the benchmark data set taken from the literature, in which its results demonstrated efficiency and effectiveness of the algorithm. After that, the proposed algorithm is implemented with the collected data from an industrial fabrication shop. The results showed that by using GA for scheduling the fabrication processes, the productivity of the spool fabrication shop with particular constraints has increased by 83 percent.
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