A Data Mining Based Solution Method for Flow Shop Scheduling Problems

Abstract

The scheduling theme which determines where and when the manufacturing actions will be performed is important to perform the activities in time, efficiently and cost-effectively. In this paper, an algorithm is proposed for the solution of a flow shop scheduling problem which holds an important place in the scheduling literature. The path relinking algorithm and data mining are used together for the solution of the flow shop scheduling problem studied here. While data mining is used for globally searching the solution space, path relinking is used for local search. Data Mining is a method which is used to extract the embedded information in a cluster that includes implicit information. Path relinking is an algorithm which advances by making binary displacements in order to convert the initial solution to the guiding solution and repeats by assigning the best obtained solution within this process as to the starting point. The efficiency of the model was tested on Taillard's flow shop scheduling problems. Consequently, it has been possible to solve the large-size problem without the considerable mathematical background. The obtained results show that the proposed method is in the competitiveness level with the other metaheuristic methods.

A new mathematical formulation and a hybrid evolutionary algorithm for re-entrant flow-shop problem with release date

“…The constraints (8)(9)(10)(11)(12)(13) are related to the sub-workshop and the constraints (14)(15)(16)(17)(18)(19)(20) are related to the main workshop. Inequality (8) reflects the same partial term related to Eq.…”

“…Constraints ( 10) and ( 11) make sure that the completion time of job i in subworkshop is before the start time of job j in the same workshop if 1 ij z = and vice versa. Relation (12) guarantees that processing of job j in sub-workshop must be started after its release date based on its position. Inequality (13) ensures that the difference between start time and completion time of job i in sub-workshop is greater than processing time of that job.…”