Despite the most of the published papers regarding the assembly line balancing problem consider straight-lines configurations, an increasing number of researchers recently point up advantages related with U-shaped lines. Literature presents only a few number of algorithms for balancing such a line type. The main difference between the straight-lines and the U-shaped lines models concerns the identification of the available operations to be assigned to a station. In the former case, each task can be assigned to a station only after its predecessors have been allocated, whereas in the latter, available operations are those whose both predecessor and successor tasks are assigned. Thus, solving approaches to balance a U-shaped line can be obtained by the application of modified techniques for straight-lines. In this paper an innovative heuristic methodology is proposed for solving the U-shaped version of the balancing problem with the aim of minimizing both labour and incompletion costs. Moreover, an algorithm for re-balancing an existing line is presented. An existing balance may change in order to accommodate modifications in cycle time, tasks completion times, precedence constraints. The necessity of a procedure for minimizing differences between the new and the initial balancing solutions is emphasized in accordance with tasks movements which involve several time consumption and costs in changing system configuration, moving and installing equipments, preparing workers, etc. The proposed model is based on a multi-objective approach to obtain valuable compromises between costs minimization and tasks re-assignment. Finally a wide experimentation in a large family of simulated scenarios is carried out to assess the suitability of the proposed procedures.
U-SHAPED ASSEMBLY LINES WITH STOCHASTIC TASKS EXECUTION TIMES: HEURISTIC PROCEDURES FOR BALANCING AND RE-BALANCING PROBLEMS / Gamberini, Rita; Grassi, Andrea; Gamberi, M.; Manzini, R.; Regattieri, A.. - STAMPA. - (2004), pp. 137-143. (Intervento presentato al convegno 2004 Advanced Simulation Technologies Conference tenutosi a Arlington VA, USA nel April 18-22, 2004).