Browsing by Subject "Parallel machine scheduling"

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Open Access
Robot move sequence determining and multiple part-type scheduling in hybrid flexible flow shop robotic cells
(Elsevier, 2016) Batur, G. D.; Erol, S.; Karasan, O. E.
We focus on the scheduling problem arising in hybrid flexible flow shops which repeatedly produce a set of multiple part-types and where the transportation of the parts between the machines is performed by a robot. The cycle time of the cell is affected by the robot move sequence, part/machine assignments and part sequences. In a hybrid flexible flow shop in which there exist one machine in the first and two machines in the second stage, the problem of determining the best cycle time is modeled as a traveling salesman problem. In order to provide a solution methodology for realistic problem instances, a Simulated Annealing based heuristic is constructed and the problem is solved using two different neighborhood structures. The results are also compared against an effective proposed lower bound value.
Open Access
Scheduling parallel CNC machines with time/cost trade-off considerations
(Elsevier, 2007) Gurel, S.; Akturk, M. S.
When the processing times of jobs are controllable, selected processing times affect both the manufacturing cost and the scheduling performance. A well-known example for such a case that this paper specifically deals with is the turning operation on a CNC machine. Manufacturing cost of a turning operation is a nonlinear convex function of its processing time. We also know that scheduling decisions are quite sensitive to the processing times. Therefore, this paper considers minimizing total manufacturing cost (F1) and total completion time (F2) objectives simultaneously on identical parallel CNC turning machines. Since decreasing processing time of a job increases its manufacturing cost, we cannot minimize both objectives at the same time, so the problem is to generate non-dominated solutions. We consider the problem of minimizing F1 subject to a given F2 level and give an effective formulation for the problem. For this problem, we prove some optimality properties which facilitated designing an efficient heuristic algorithm to generate approximate non-dominated solutions. Computational results show that proposed algorithm performs almost equal with the GAMS/MINOS commercial solver although it spends much less computation time.