A genetic algorithm for balancing and sequencing of mixed-model two-sided assembly line with unpaced synchronous transfer

Abstract

Research on the assembly line balancing problem has been continuously incorporated the characteristics of actual production lines without considering the mixed-model two-sided assembly line with unpaced synchronous transfer, which is common in body shops of cars or trucks. This study attempts to model a mixed-model two-sided assembly line balancing and sequencing problem with unpaced synchronous transfer, and designs a genetic algorithm to solve this problem. First, to describe the process whereby model sequence and its execution, station and its number, and the process time caused by task allocation lead to the variable output of an unpaced synchronous line, a model without an observation point restriction is proposed. Based on this, a mathematical model of a balancing and sequencing problem of a mixed-model two-sided assembly line with an unpaced synchronous transfer is established, in which the balancing problem is aimed at Type-II. Then, an improved genetic algorithm adapted to the complexity of the problem is proposed. The algorithm designs a combination and evaluation mechanism to ensure that the solution populations of the balancing and sequencing problems are sufficiently combined and evaluated in each iteration to improve efficiency. The proposed algorithm is illustrated using a small numerical example. Finally, the algorithm is experimentally investigated using a set of test cases and several comparison algorithms. The experimental results show that the combination and evaluation mechanism is suitable for these problems, especially for large-sized cases, and that the proposed algorithm is effective and has better performance than the comparison algorithms.