Integrated cell formation and part scheduling: A new mathematical model along with two meta-heuristics and a case study for truck industry

This paper proposes a new linearized mathematical model to solve integrated cell formation and job scheduling problem. The model aims to minimize the exceptional elements, voids and the make-span of the jobs. The results of test problems show that the proposed model is very effective to obtain best solutions for small sized problems in reasonable computation times. However, due to the NP-hard nature of the considered problem, the best solutions couldn’t be obtained in acceptable times for large sized test problems whereas the real-life applications of the problem addressed here are often much larger in size. To meet the requirement of solving larger sized problems, Genetic Algorithm, which is, today, considered as one of the artificial intelligence and machine learning technique and Marine Predators Algorithm as a new and a nature-inspired metaheuristic, are proposed. The success of the algorithms was investigated and compared. The test results reveal the fact that the Marine Predators algorithm with optimized parameters has a high potential to solve real life problems. At last, an attempt is made to re-design an existing real-life production system by the proposed algorithms. Eventually, a considerable improvement is obtained on performance compared to the current situation of the system.