A New Crab Shell Search Algorithm for Optimal Assembly Sequence Generation

Abstract

Assembly Sequence Planning (ASP) problem is one of the multi-objective optimization problems, where more than one objective function has to optimize to obtain quality optimal sequence. Initially, for ASP problem researchers applied mathematical models to obtain optimal sequences. Later, soft computing techniques are developed to obtain the optimal assembly sequences due to its ease ness in implementation. At the same time, some of the researchers developed CAD based and knowledge-based methods to obtain the optimal sequences, which consumes more search space during execution of the algorithm. Keeping the above considerations in mind and the advantages with artificial intelligence techniques, in this paper a new algorithm namely Crab Shell Search (CSS) algorithm has been proposed to obtain the optimal assembly sequences. This algorithm is developed mainly based on how the crab will search for a suitable shell in the shore to survive from the foreign bodies. The proposed methodology is applied to the different industrial products, the results obtained from the algorithm are compared with different well-known algorithms like Genetic Algorithm (GA), Ant Colony optimization (ACO) Algorithm, Enhanced Genetic Algorithm (EGA) and Memetic Algorithm (MA) to test the performance of the algorithm.