Abstract
This study proposes software that allows the user to solve the Job Shop Scheduling Problem (JSSP) with makespan minimization to support the teaching and learning of the JSSP, one of the main scheduling problems in the Operations Research literature. The application allows the user to enter instance data, solve it using four different mixed integer linear programming (MILP) models and evaluate the results in graphical form through an interactive Gantt chart and tabular form. The computational tool was developed in Python, using Streamlit, Pyomo, and GLPK as main libraries, and it can be accessed free via the internet. In addition, its source code is available for anyone to reproduce, redistribute and modify under the terms of the GPL v3.0. This work demonstrates the resolution of a 5 × 3 size problem through the four models available in the application, which observed four different optimal solutions. However, the performance of the disjunctive models is superior to the others in the execution time. Furthermore, it was found that the time-indexed model may not be useful in larger problems.
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da Silva Júnior, A.C., Loch, G.V., dos Santos, M. (2023). A Proposal of Web Application for the Study and Resolution of the Job Shop Problem with Makespan Minimization Via Mixed Integer Linear Programming. In: Gonçalves dos Reis, J.C., Mendonça Freires, F.G., Vieira Junior, M. (eds) Industrial Engineering and Operations Management. IJCIEOM 2023. Springer Proceedings in Mathematics & Statistics, vol 431. Springer, Cham. https://doi.org/10.1007/978-3-031-47058-5_2
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