An exact solution method for seruscheduling problems with multiple rate-modifying activities and learning effect

This study investigates two seruscheduling problems in a seruproduction system (SPS) with multiple rate-modifying activities and DeJong's learning effect to minimise the total completion time and the total waiting time. Upon reformulating two seruscheduling problems to assignment problems, the calculation time is confirmed; these two seruscheduling problems can be solved in polynomial time if the job allocation vector is given in advance. Then, a general exact solution method is proposed to obtain the optimal schedule. Computational experiments and sensitivity analysis on learning effect are also designed to test the performance of proposed exact solution method. The results indicate that the frequency of rate-modifying activity is not the more the better, nor the less the better in improving the production efficiency, a balance between modifying rate and modifying times should also be considered in practical SPS production. The proposed exact solution method can provide the optimal solution in reasonably implementing rate-modifying activity strategies and scheduling jobs to reach the shortest total completion time or job waiting time. This study will instructively help SPS shorten production cycle, improve productivity and order responsiveness to some extent. [Received: 28 December 2021; Accepted: 28 December 2022]