Flexible job-shop scheduling problem with sequencing flexibility for just-in-time production systems

Abstract

Scheduling in a flexible job-shop environment is a crucial task that allows the smooth flow of materials. Traditionally, this problem considers a predetermined sequence of operations and due dates to deliver the jobs. In this paper, a new formulation of the Flexible Job-Shop Scheduling problem is presented. In the proposed model, flexible sequences for the jobs are allowed to enable more alternatives for scheduling. Additionally, just-in-time approach is considered in order to complete each job. Hence, the problem allocates operations to machines and sequence them according to precedence relationships. Moreover, jobs' deliveries need to be on time to satisfy customer's requirements and reduce storage costs. Therefore, a mixed-integer linear programming model is formulated to minimize the sum of weighted earliness and weighted tardiness simultaneously. The model is implemented in a numerical experiment to show its applicability. The proposed model is intended to be used in production systems that are just-in-time oriented.