Deliktaş, DeryaÖzcan, EnderÜstün, ÖzdenTorkul, Orhan2024-05-072024-05-0720242352-3409https:/dx.doi.org10.1016/j.dib.2023.109946https://hdl.handle.net/20.500.12451/11788This data article presents a description of a benchmark dataset for the multi-objective flexible job shop scheduling problem in a cellular manufacturing environment. This problem considers intercellular moves, exceptional parts, sequence-dependent family setup and intercellular transportation times, and recirculation requiring minimization of makespan and total tardiness simultaneously. It is called a flexible job shop cell scheduling problem with sequence dependent family setup times and intercellular transportation times (FJCS-SDFSTs-ITTs) problem. The dataset has been developed to evaluate the multi-objective evolutionary algorithms of the FJCS-SDFSTs-ITTs problems that are presented in 'Evolutionary algorithms for multi-objective flexible job shop cell scheduling'. The dataset contains forty-three benchmark instances from 'small' to 'large', including a large real-world problem instance. Researchers can use the dataset to evaluate the future algorithms for the FJCS-SDFSTs-ITTs problems and compare the performance with the existing algorithms.eninfo:eu-repo/semantics/openAccessCell SchedulingFlexible Job Shop SchedulingMulti-objective ModelSequence-dependent Family Setup TimesIntercellular Transportation TimesExceptional and Reentrant PartsArticle5210.1016/j.dib.2023.109946Q1N/A