Order acceptance/rejection policies in determining the sequence in mixed model assembly lines

This study presents a decision support system for order acceptance/rejection in a Make-to-Order production environment with the mixed model assembly line approach. Indeed, variety of orders is the parameter under investigation herein. When the company does not have sufficient capacity or the required resources to accept the entirety of all new arrival orders, the following steps are proposed: At first, the customers are prioritized based on their corresponding profit values (at present and in the future) whereas other orders are rejected by the top manager along with some undesirable ones. Then, prices and delivery dates of the non-rejected orders are determined via a mathematical programming model. Quality levels are also reported to the customers based upon which they are allowed to select their desired blend of main components. Afterwards, in the case of customer’s lack of satisfaction with the offered price and due date, further negotiation is proposed. Finally, if the negotiation leads to an agreement, the order is accepted and added to the production schedule of the shop floor. The schedule of accepted orders is performed based on minimizing the work overload. The present study presumes that the processing times of the tasks are affected by both learning effect and deterioration of the jobs, simultaneously. In the last section of the study afoot, numerical experiments as well as the corresponding methodology are presented in order to solve the models. Moreover, a simulated annealing algorithm is utilized to solve the problem in a large scale with little computational time. Numerical experiments confirm that the simulated annealing algorithm tends to yield rather fine results with little discrepancy compared to those of the exact algorithm in small and medium size.