The cyclic job-shop scheduling problem: The new subclass of the job-shop problem and applying the Simulated annealing to solve it
This addresses scheduling inefficiencies in cyclic production planning for manufacturing or operations research, though it appears incremental as it builds on existing job-shop problems with a new subclass and method.
The paper tackles the cyclic job-shop scheduling problem by introducing a new subclass called the cyclic job-shop problem of order k, where k is the number of reiterations, and finds that planning the entire cycle is more effective than planning a single iteration, with experiments showing significant efficiency increases using Simulated Annealing.
In the paper, the new approach to the scheduling problem are described. The approach deals with the problem of planning the cyclic production and proposes to consider such scheduling problem as the cyclic job-shop problem of the order k, where k is the number of reiterations. It was found out that planning of only one iteration of the loop is less effective than planning of the entire cycle. To the experimental research, a number of test instances of the job-shop scheduling problem by Operation Research Library were used. The Simulated Annealing was applied to solve the instances. The experiments proved that the approach proposed allows increasing the efficiency of cyclic scheduling significantly.