Simultaneous solving of balancing and sequencing problems with station-dependent assembly times for mixed-model assembly lines

In spite of many studies, investigating balancing and sequencing problems in Mixed-Model Assembly Line (MMAL) individually, this paper solves them simultaneously aiming to minimize total utility work. A new Mixed-Integer Linear Programming (MILP) model is developed to provide the exact solution of the problem with station-dependent assembly times. Because of NP-hardness, a Simulated Annealing (SA) is applied and compared to the Co-evolutionary Genetic Algorithm (Co-GA) from the literature. To strengthen the search process, two main hypotheses, namely simultaneous search and feasible search, are developed contrasting Co-GA. Various parameters of SA are reviewed to calibrate the algorithm by means of Taguchi design of experiments. Numerical results statistically show the efficiency and effectiveness of the proposed SA in terms of both the quality of solution and the time of achieving the best solution. Finally, the contribution of each hypothesis in this superiority is analyzed.

Figure optionsDownload as PowerPoint slideHighlights
► A new version of MMAL balancing/sequencing problem: station-dependent assembly times.
► Developing a new MILP model to simultaneously solve problems minimizing utility work.
► Because of NP-hardness a Simulated Annealing, tuned via Taguchi method, is used.
► The SA is equipped with two main ideas, developed against Co-GA (from the literature).
► The SA is more efficient than Co-GA and its results are very close to exact solutions.