A hybrid ant colony algorithm for U-line balancing and rebalancing in just-in-time production environment

Abstract U-line balancing is an important problem for designing a new U-line. It is about combining a finite set of tasks to form workstations optimally with the restriction of given precedence relationships in a new U-line. As the demand varies, the U-line should be rebalanced to eliminate waste and improve the production efficiency as part of just-in-time principles. If all machines can be moved freely, the rebalancing problem equals to the balancing problem. In practice, some machines are stationary or need certain moving cost. In this paper, U-line rebalancing problem is formalized with respect to minimization the moving cost of machines and labor cost. The walking time of operators is considered to avoid generating awkward walking path. A new hybrid algorithm of ant colony optimization and filtered beam search is presented to solve the problem. The hybrid algorithm adopts the framework of ant colony optimization. In the process of constructing path, each ant explores several nodes for one step and chooses the best one by global and local evaluation at a given probability. Computational results show that the proposed algorithm performs quite effectively for solving U-line balancing problems in the literature by comparing to the existing solutions. Finally, the proposed algorithm for solving U-line rebalancing problem is demonstrated with an example and also yields optimal solutions.