A fuzzy-stochastic programming approach for a resource-constrained project scheduling problem in the production of seismic isolators

Subulan K., Waris Shafique A.

International IDU Engineering Symposium, İzmir, Turkey, 15 - 17 November 2023, pp.2

  • Publication Type: Conference Paper / Summary Text
  • City: İzmir
  • Country: Turkey
  • Page Numbers: pp.2
  • Dokuz Eylül University Affiliated: Yes


The manufacturing system of seismic isolators has a project-based production process and therefore, it is generally required to prepare a project plan or schedule for their production under restricted resources such as machinery and manpower as well as uncertainty. Based on this motivation, a well-known project scheduling problem in the literature, which is named a single-mode resource-constrained project scheduling (RCPS) problem is investigated in this study for the production project of seismic isolators in large-sized manufacturing company. First, a deterministic optimization model which is formulated as an integer program is presented to solve the examined problem under certain environments. Then, the uncertainties in the activity durations and the resource capacities (or availabilities) are also considered by making use of hybridizing the fuzzy mathematical programming and scenario-based stochastic programming approaches. In addition to these uncertain project parameters/inputs, the project schedules/outputs (i.e., completion times of the activities) are also considered as uncertain decision variables and represented by triangular fuzzy numbers. First, the previously mentioned deterministic optimization model is solved separately for each scenario and then, its optimization results are also compared to the results of a constraint programming model. Therefore, it is proven that both of the integer programming and constraint programming models are able to generate the same optimization results within reasonable computing times. Afterwards, a fuzzy-stochastic programming model that integrates all of these scenarios (i.e., pessimistic, most likely, and optimistic cases) in a single optimization model is also formulated and then converted into its crisp equivalent form to minimize the expected value of the total project duration (i.e., makespan) and to obtain fuzzy project schedules under different probability values of these scenarios. Therefore, different types of uncertainties can be handled simultaneously by making use of this fuzzy-stochastic program. Finally, the computational study has shown that efficient fuzzy-stochastic optimization results/project schedules can be provided via the proposed fuzzy-stochastic programming approach. Moreover, the generated fuzzy completion times of the project activities are presented to the production project managers of the seismic isolator manufacturing company for providing managerial insights.