Mathematical Modelling and Heuristic Approaches to Job-shop Scheduling Problem with-based Continuous Flow

Job-shop Scheduling Problem (JSP) with conveyor-based Continuous Flow Transporters (CFTs) is a general production scheduling problem in the flexible manufacturing systems in practical electronics manufacturing industry. In such a problem setting, the jobs are processed on the machines which are connected in series via the conveyor, and the conveyor segments serve as CFTs by transferring the jobs to the machines automatically. The jobs have to obey First In First Out (FIFO) constraint and limited buffer constraint during their transportation and processing in the system. The objective of scheduling is to find an order in which the jobs enter into the system such that the makespan is minimized. This paper investigates the optimization of the problem by the mathematical modelling and heuristic approaches. The Mathematical Programming (MP) model of the problem is presented and it is used as an exact solution approach for solving small instances optimally. To solve larger problem, the Simulated Annealing (SA) algorithm with a solution perturbation Neighbourhood Generation Scheme (NGS) is proposed to generate near-optimal solutions. The performance of the two approaches to the problem is evaluated by conducting computational experiment. The performance of the MP approach to the problem is numerically investigated, and the performance of the proposed SA algorithm with the solution perturbation NGS is evaluated by comparing against the SA algorithm with two conventional NGSs. The computational results show the superiority of the proposed algorithm over the conventional ones. Furthermore, a comparative study on the performance of the MP approach and the heuristic approach to the problem is implemented. In addition, sensitivity analysis is conducted to investigate the effects of buffer capacity on the performance of the manufacturing system.