Developing a bi-objective schedule for an online cellular manufacturing system in an MTO environment

• Published in: Soft computing (Berlin, Germany) Germany), 2022, Vol.26 (2), p.807-828
• Main Authors: Kazemi, Mohammad, Sadegheih, Ahmad, Lotfi, Mohammad Mahdi, Vahdat, Mohammad Ali
• Format: Article
• Language: English
• Subjects: Artificial Intelligence; Computational Intelligence; Control; Engineering; Mathematical Logic and Foundations; Mechatronics; Robotics; Soft Computing in Decision Making and in Modeling in Economics
• ISSN: 1432-7643; 1433-7479
• DOI: 10.1007/s00500-021-06402-z

So far, a great bulk of research has been dedicated to demand fluctuations in the make-to-order (MTO) environment, and several solutions have been proposed. In contrast, cellular layouts have received little attention from researchers. Also, in studies on dynamic cell production systems, the concept of dynamics is limited to the possibility of making changes between periods. This paper presents a new mathematical model to create an integrated system of order prioritizing, capacity measurement, and scheduling for dealing with new orders in MTO environments arranged by a cellular manufacturing layout. In this model, it is possible to negotiate the price and delivery time. The periods are also considered to be connected, and unlike the existing dynamic cellular manufacturing systems (DCMSs), it is possible to receive an order at any moment. Moreover, machine relocation is allowed with regard to the time of relocation during the periods. Another notable feature is the alternative routing for parts and cell formation (CF) at the same time as scheduling. The proposed model has two objectives including a) maximizing the profit and b) maximizing the number of orders accepted based on their priorities. The bi-objective model for small sizes has been solved by GAMS software using the augmented epsilon-constraint method. The effects of key parameters as well as some important features of the model, such as the possibility of checking the acceptance/rejection of a new order during the program, are addressed. Generally, the proposed model is able to develop a DCMS in an online cellular manufacturing system (OCMS). The results of sensitivity analysis show that the integration of CF, GS, order acceptance, pricing, and delivery time in a mathematical model simultaneously can significantly improve system performance and increase system profits. Finally, an NSGA-II algorithm is developed to solve the problem in larger sizes. To verify the computational effectiveness of the employed NSGA-II in comparison with a CPLEX solver, its performance is evaluated using two methods.