A chance-constrained multi-objective model for final assembly scheduling in ATO systems with uncertain sub-assembly availability

A chance-constraint multi-objective model under uncertainty in the availability of subassemblies is proposed for scheduling in ATO systems. The on-time delivery of customer orders as well as reducing the company's cost is crucial; therefore, a three-objective model is proposed including the minimization of1) overtime, idletime, change-over, and setup costs, 2) total dispersion of items’ delivery times in customers’ orders, and 3) tardiness and earliness costs.In order to reduce the involved risk,the uncertainty in the subassembly availabilities is addressed via a chance-constrained programming. The lexicographic method is employed to solve the model. The performance and validity is then evaluated using the real data from an electrical company. Notably, the decision maker can draw the appropriate results by a priority establishment between the costs and delivery time objectives. Moreover, formulating the existing uncertainty in the subassembly availabilities helps avoiding delay in the orders’ completion dates. Finally, applying joint lot size policy leads to a more proper scheduling of assembly sequence.