This paper considers a scheduling problem in a two-machine flowshop with outsourcing strategy incorporated. The jobs can be either processed in the first machine or outsourced to outside subcontractors. This paper wants to determine which jobs to be processed in-house and which jobs to be outsourced. If any job is decided to be outsourced, then an additional outsourcing cost is charged The objective of this paper is to minimize the sum of scheduling cost and outsourcing cost under a budget constraint. At first this paper characterizes some solution properties, and then it derives solution procedure including DP (Dynamic Programming) and B&B (Branch-and-Bound) algorithms and a greedy-type heuristic. Finally the performance of the algorithms are evaluated with some numerical tests.

This paper considers a 2-stage assembly flowshop scheduling problem where each job is completed by assembling multiple components. The problem has the objective measure of minimizing total completion time. The problem is shown to be NP-complete in the str

  This paper improves algorithms for an assembly-type flowshop scheduling problem in which each job is to assemble two types of components and makespan is the objective measure. For the assembly, one type of the components is outsourced with job-dependent

  In this paper, we study flowshop scheduling problems with availability constraints. In such problems, n jobs have to be scheduled on m machines sequentially under assumption that the machines are unavailable during some periods of planning horizon. The

  This paper considers an assembly-type flowshop scheduling problem in which each job is assembled with two types of components. One type of the components is outsourced with positive lead time but the other type is fabricated in-house at the first stage.

This paper considers a scheduling problem concerned with an assembly system where two components are first treated in their own parallel machines and then pulled to be assembled into a final product at a single assembly machine. The objective measure is t