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Alvarez-Miranda, E., Pereira, J., Torrez-Meruvia H., & Vila, M. (2021). A Hybrid Genetic Algorithm for the Simple Assembly Line Balancing Problem with a Fixed Number of Workstations. Mathematics, 9(17), 2157.
Abstract: The assembly line balancing problem is a classical optimisation problem whose objective is to assign each production task to one of the stations on the assembly line so that the total efficiency of the line is maximized. This study proposes a novel hybrid method to solve the simple version of the problem in which the number of stations is fixed, a problem known as SALBP-2. The hybrid differs from previous approaches by encoding individuals of a genetic algorithm as instances of a modified problem that contains only a subset of the solutions to the original formulation. These individuals are decoded to feasible solutions of the original problem during fitness evaluation in which the resolution of the modified problem is conducted using a dynamic programming based approach that uses new bounds to reduce its state space. Computational experiments show the efficiency of the method as it is able to obtain several new best-known solutions for some of the benchmark instances used in the literature for comparison purposes.
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Alvarez-Miranda, E., Pereira, J., Vargas, C., & Vila, M. (2022). Variable-depth local search heuristic for assembly line balancing problems. Int. J. Prod. Res., 61(9), 3103–3121.
Abstract: Assembly lines are production flow systems wherein activities are organised around a line consisting of various workstations through which the product flows. At each station, the product is assembled through a subset of operations. The assembly line balancing problem (ALBP) consists of allocating operations between stations to maximise the system efficiency. In this study, a variable-depth local search algorithm is proposed for solving simple assembly line balancing problems (SALBPs), which are the most widely studied versions of the ALBP. Although the state-of-the-art techniques for solving the SALBP consist of exact enumeration-based methods or heuristics, this paper proposes a local search-based heuristic using variable-length sequences that allow the solution space to be efficiently explored. The proposed algorithm improves the best solution known for multiple instances reported in the literature, indicating that its efficiency is comparable to those of the state-of-the-art method for solving the SALBP. Moreover, the characteristics of the instances for which the proposed procedure provides a better solution than previously reported construction procedures are investigated.
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