Mixed-model assembly line balancing with smoothing approach based on tabu search algorithm

Abstract

Mixed-model assembly lines are needed for the assembly of products with a variety of models at comparatively lower costs. The design of such lines requires the work to be done at stations well balanced, satisfying the constraints such as time, space and location for optimal productivity and efficiency. This paper presents a heuristic algorithm for the mixed-model assembly line balancing problem to minimize the number of stations for a given cycle time. The proposed algorithm further reduces time discrepancies among stations due to differences in times for common operations of different models by using a smoothing approach which is based on the tabu search algorithm.