Apply GRASP Aalgorithm to Solve the Flow shop Scheduling without Intermediate Queues Using Traveling Salesman Problem

The aim of this paper is to minimize the period of manufacturing in the flow shop scheduling problem without intermediate queues. Scheduling problem without intermediate queues occurs when the process of one job should be processed on the machines from start to finish without interrupting. Since this structure is similar to standard traveling salesman problem, in the present study, a new approach was applied to calculate the tardiness, in which the tardiness matrix obtained from salesman problem is used to find the optimal sequence of operations that has a shortest distance time. Furthermore, the greedy random adaptive search algorithm (GRASP) as meta-heuristic algorithm is applied to solve the sequencing workflow without queues central workshop problem and its performance is compared to the ant colony algorithm after determining the its parameters through full factorial experimental design method.