Discrete electromagnetism-like mechanism algorithm for assembly sequences planning

Assembly sequence planning (ASP) plays an important role in digital manufacturing. It is a combinatorial optimisation problem with strong constraints aiming to work out a specific sequence to assemble together all components of a product. The connector-based ASP, which uses the connector to simplify the complex assembly problem, is one of the most important and hardest types. In order to solve this problem effectively, a discrete electromagnetism-like mechanism (DEM) algorithm is proposed. A charge formula and a force formula are redefined in DEM algorithm. An adjacency list is applied to handle the precedence relationship and prevent infeasible solutions. Two movements based on path relinking are employed. Moreover, with two different guided mutations, the population diversity can be guaranteed. Five examples are used to test and evaluate the performance of DEM. The comparisons among the proposed DEM, traditional genetic algorithms (GAs), guided GAs, memetic algorithms and artificial immune systems show that DEM outperforms among these algorithms in terms of running time, computation accuracy, convergence speed and parameter robustness.