Solving type-2 assembly line balancing problem with fuzzy binary linear programming

This paper deals with the use of fuzzy set theory as a viable alternative method for modelling and solving the stochastic assembly line balancing problem. This paper presents a fuzzy extension of the simple assembly line balancing problem of type 2 (SALBP-2) with fuzzy job processing times since uncertainty, variability, and imprecision are often occurred in real-world production systems. The job processing times are formulated by triangular fuzzy membership functions using their statistical distributions. This study proposes to solve a Fuzzy Binary Linear Problem (FBLP) with fuzzy coefficients in the objective function and in a constraint. Finally, the effect of the unbalancing of a station in a real case study has been investigated in order to consider different scenarios. In particular, four different scenarios were studied considering the balanced and unbalanced line with deterministic and stochastic job processing times. The results obtained showed that the use of a fuzzy approach allows to take in account the effect of the job processing time variability demonstrating the validity of the proposed model.