Scheduling of multi-component products in a two-stage flexible flow shop

• The first stage consists of several parallel machines in site I with different speed in processing components and one machine in site II, and the second stage consists of two dedicated assembly lines.
• The products that compose of only single-process components are assigned to the first assembly line and products that compose of at least a two-process component are assigned to the second assembly line.
• Due to the complexity of solving flexible flow shop problems, we consider this type of problem in NP-Hard problem family and suggest a metheuristic method which is created by combinations of simulated annealing (SA) and imperialist competitive algorithms (ICA).

In this research, the problem of scheduling and sequencing of two-stage assembly-type flexible flow shop with dedicated assembly lines, which produce different products according to requested demand during the planning horizon with the aim of minimizing maximum completion time of products is investigated. The first stage consists of several parallel machines in site I with different speeds in processing components and one machine in site II, and the second stage consists of two dedicated assembly lines. Each product requires several kinds of components with different sizes. Each component has its own structure which leading to difference processing times to assemble. Products composed of only single-process components are assigned to the first assembly line and products composed of at least a two-process component are assigned to the second assembly line. Components are placed on the related dedicated assembly line in the second phase after being completed on the assigned machines in the first phase and final products will be produced by assembling the components. The main contribution of our work is development of a new mathematical model in flexible flow shop scheduling problem and presentation of a new methodology for solving the proposed model. Flexible flow shop problems being an NP-hard problem, therefore we proposed a hybrid meta-heuristic method as a combination of simulated annealing (SA) and imperialist competitive algorithms (ICA). We implement our obtained algorithm and the ones obtained by the LINGO9 software package. Various parameters and operators of the proposed Meta-heuristic algorithm are discussed and calibrated by means of Taguchi statistical technique.

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