Benchmark data instances for the Multi-Objective Flexible Job shop Scheduling Problem with Worker flexibility
Description
The proposed data consist of benchmark test instances for the Multi-Objective Flexible Job shop Scheduling Problem with Worker flexibility (MO-FJSPW). To the best of our knowlage, the MO-FJSPW is proposed for the first time by (Gong et al., 2017) [DOI:10.1080/00207543.2017.1388933], where the authors created data instances only for the total worker flexibility case: any machine can be operated by all the workers. That is why, we propose new benchmark data instances named “SFJW” and “MFJW” considering the MO-FJSPW with the partial worker flexibility case: each machine can be processed by a sub-set of workers.
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Steps to reproduce
The constructing method of the MO-FJSPW benchmarks is shown in Algorithm 1 in which F denotes the default data extracted from (Fattahi et al., 2007) [DOI:10.1007/s10845-007-0026-8] instances. The available worker set Wijk for each available machine Mijk is generated with the method of uniform distribution, where Wijk > 0 and Wijk <= size(number of workers). The processing time Pijks is determined by the uniform distribution method, where Pijks >= minProcessTime(Mij) and Pijks <= maxProcessTime(Mij). -------------------------------------------------------------------------------------------------- Algorithm 1: benchmark data instances construction for the MO-FJSPW Get the default input parameters from F, number of: jobs, operations per job and machines Add the number of workers For i = 1 : size(jobs) For j = 1 : size(operations per job) Get the operation Oij, its available machine set Mij, minProcessTime(Mij) and maxProcessTime(Mij) For k = 1 : size(Mij) Generate the available worker set Wijk for each available machine Mijk with uniform distribution, where Wijk > 0 and Wijk <= size(number of workers) For s = 1 : size(Wijk) Generate the processing time Pijks for each available worker Wijks with uniform distribution, where Pijks >= minProcessTime(Mij) and Pijks <= maxProcessTime(Mij) End For End For End For End For --------------------------------------------------------------------------------------------------