A multi-objective imperialist competitive algorithm for integrating intra-cell layout and processing route reliability in a cellular manufacturing system

In this article, a novel bi-objective integer model is presented to integrate reliability and intra-cell layout in designing a cellular manufacturing system (CMS). Minimising the total costs (e.g. inter and intra-cell material handling, machine overhead and operation, and setting up routes) is the first objective with considering operation time, operation sequence, intra-cell layout, alternative process routing, routes selection, machines capacity, parts demand and parts movements in batches. Maximising the processing routes reliability is the second objective. The presented model is capable of modelling different failure characteristics including a decreasing, increasing, or constant value for machine failure rate. An illustrative example is solved to represent the capability of the presented model using the ε-constraint method in order to demonstrate the conflict between the maximum value of the system reliability and the total costs of the system. Next, a multi-objective imperialist competitive algorithm (MOICA) is employed to find near-optimal solutions for medium- and large-sized test problems. Also, the efficiency of the proposed MOICA is revealed by comparison with the performance of a non-dominated sorting genetic algorithm (NSGA-II). The computational results demonstrate that the performance of the proposed MOICA is superior to the NSGA-II. Furthermore, a real-world case study is conducted to validate the proposed model.