Spool fabrication shop is an intermediate phase in the piping process for construction projects. The delivery of pipe spools at the right time in order to be installed in the site, is very important. Therefore, effective scheduling and control of the fabrication shop has a direct effect on the productivity and successfulness of the whole construction projects. This research developed a genetic algorithm (GA) in order to generate a feasible and near-optimal schedule for the operational level of pipe spool fabrication shop based on the concepts and methods of job shop scheduling problems. In the proposed algorithm, an improved chromosome representation is used to conveniently represent a schedule for the fabrication shop. Operation-based global selection and Operation-based local selection are designed to generate high-quality initial population in the initialization stage. To adapt to the special chromosome structures and the characteristics of the problem, precedence order-based crossover (POX), two-point crossover, and uniform crossover are used. In addition, different mutation operators for operation sequence part and machine assignment part of the chromosome are used. The data which consist of operations processing time, and dimension of spools and stations are collected from an industrial fabrication shop. The proposed algorithm is applied by using the collected data to obtain a feasible and near-optimal schedule for the operational level of pipe spool fabrication shop. The results showed that the productivity of the fabrication shop by using the proposed algorithm for scheduling fabrication processes has increased to 178 percent.
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