This paper addresses a multi-objective mixed-model two-sided assembly line balancing and worker assignment with bottleneck analysis when the task times are dependent on the worker’s skill. This problem is known as NP-hard class, thus, a hybrid cyclic-hierarchical algorithm is presented for solving it. The algorithm is based on Particle Swarm Optimization (PSO) and Theory of Constraints (TOC) and consists of two stages. In stage one, simultaneous balancing and worker assignment are studied. In stage two, bottleneck analysis and product-mix determination are carried out. In addition, a bi-level mathematical model is presented to describe the problem. The following objective functions are verified in this paper: (1) minimizing the number of mated-stations (2), minimizing the number of stations (3) minimizing the human costs (4) minimizing the weighted smoothness index and (5) maximizing the total profit. In addition to the proposed algorithm, another algorithm, which is based on the simulated annealing and the theory of constraints, is developed to compare the performance of the proposed algorithm in terms of the running time and the solution quality over the different benchmarked test problems. Moreover, several lower bounds are developed for the number of the stations and the number of the mated-stations. The results show and support the efficiency of the proposed approaches.
