A psycho-clonal-algorithm-based approach to the solve operation sequencing problem in a CAPP environment

Pertaining to the intricacies involved in the formulation of an optimal process planning system, operation sequencing has been recognized as a complex and crucial task to be accomplished. The operation sequencing problem determines the preferred order to perform a set of selected operations that satisfies the precedence constraints along with the satisfaction of the optimization goals. In general, the problem is characterized by its combinatorial nature and complex precedence relations that make it computationally complex. A psycho-clonal-algorithm-based approach has been proposed in this paper to solve optimally the operation sequencing problem. The objective function has been made more comprehensive for the parts types of varying complexities. This approach is an extension of the artificial immune system (AIS) approach and inherits its characteristics from the Maslow's need hierarchy theory related to psychology. The various need levels present in the algorithm help in maintaining the viability of solution, whereas the path towards optima is revealed by the trait of affinity maturation. Effectiveness of the algorithm is authenticated by solving the problems of varying complexities cited in the literature and comparing its performance with other established metaheuristic approaches.