The manufacturing system of seismicisolators has a project-based production process and therefore, it is generallyrequired to prepare a project plan or schedule for their production underrestricted resources such as machinery and manpower as well as uncertainty.Based on this motivation, a well-known project scheduling problem in theliterature, which is named a single-mode resource-constrained projectscheduling (RCPS) problem is investigated in this study for the productionproject of seismic isolators in large-sized manufacturing company. First, adeterministic optimization model which is formulated as an integer program ispresented to solve the examined problem under certain environments. Then, theuncertainties in the activity durations and the resource capacities (oravailabilities) are also considered by making use of hybridizing the fuzzymathematical 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 uncertaindecision variables and represented by triangular fuzzy numbers. First, thepreviously mentioned deterministic optimization model is solved separately foreach scenario and then, its optimization results are also compared to theresults of a constraint programming model. Therefore, it is proven that both ofthe integer programming and constraint programming models are able to generatethe same optimization results within reasonable computing times. Afterwards, afuzzy-stochastic programming model that integrates all of these scenarios(i.e., pessimistic, most likely, and optimistic cases) in a single optimizationmodel is also formulated and then converted into its crisp equivalent form tominimize the expected value of the total project duration (i.e., makespan) and toobtain fuzzy project schedules under different probability values of thesescenarios. Therefore, different types of uncertainties can be handledsimultaneously by making use of this fuzzy-stochastic program. Finally, thecomputational study has shown that efficient fuzzy-stochastic optimizationresults/project schedules can be provided via the proposed fuzzy-stochasticprogramming approach. Moreover, the generated fuzzy completion times of theproject activities are presented to the production project managers of theseismic isolator manufacturing company for providing managerial insights.