Browsing by Subject "Makespan"

Now showing 1 - 5 of 5

Open Access
A new bounding mechanism for the CNC machine scheduling problems with controllable processing times
(Elsevier, 2005) Kayan, R. K.; Akturk, M. S.
In this study, we determine the upper and lower bounds for the processing time of each job under controllable machining conditions. The proposed bounding scheme is used to find a set of discrete efficient points on the efficient frontier for a bi-criteria scheduling problem on a single CNC machine. We have two objectives; minimizing the manufacturing cost (comprised of machining and tooling costs) and minimizing makespan. The technological restrictions of the CNC machine along with the job specific parameters affect the machining conditions; such as cutting speed and feed rate, which in turn specify the processing times and tool lives. Since it is well known that scheduling problems are extremely sensitive to processing time data, system resources can be utilized much more efficiently by selecting processing times appropriately.
Open Access
Optimal allocation and processing time decisions on non-identical parallel CNC machines: ε{lunate}-constraint approach
(Elsevier, 2007-12-01) 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. In this paper, we deal with making optimal machine-job assignments and processing time decisions so as to minimize total manufacturing cost while the makespan being upper bounded by a known value, denoted as -constraint approach for a bicriteria problem. We then give optimality properties for the resulting single criterion problem. We provide alternative methods to compute cost lower bounds for partial schedules, which are used in developing an exact (branch and bound) algorithm. For the cases where the exact algorithm is not efficient in terms of computation time, we present a recovering beam search algorithm equipped with an improvement search procedure. In order to find improving search directions, the improvement search algorithm uses the proposed cost bounding properties. Computational results show that our lower bounding methods in branch and bound algorithm achieve a significant reduction in the search tree size that we need to traverse. Also, our recovering beam search and improvement search heuristics achieve solutions within 1% of the optimum on the average while they spent much less computational effort than the exact algorithm.
Open Access
Parallel machine scheduling subject to machine availability constraints
(2006) Sevindik, Kaya
Within a planning horizon, machines may become unavailable due to unexpected breakdowns or pre-scheduled activities. A realistic approach in constructing the production schedule should explicitly take into account such periods of unavailability. This study addresses the parallel machine-scheduling problem subject to availability constraints on each machine. The objectives of minimizing the total completion time and minimizing the maximum completion time are studied. The problems with both objectives are known to be NP-hard. We develop an exact branch-and-bound procedure and propose three heuristic algorithms for the total completion time problem. Similarly, we propose exact and approximation algorithms also for the maximum completion time problem. All proposed algorithms are tested through extensive computational experimentation, and several insights are provided based on computational results.
Open Access
Scheduling with artificial neural networks
(1993) Gürgün, Burçkaan
Artificial Neural Networks (ANNs) attempt to emulate the massively parallel and distributed processing of the human brain. They are being examined for a variety of problems that have been very difficult to solve. The objective of this thesis is to review the current applications of ANNs to scheduling problems and to develop a parallelized network model for solving the single machine mean tardiness scheduling problem and the problem of finding the minimum makespan in a job-shop. The proposed model is also compared with the existing heuristic procedures under a variety of experimental conditions.
Open Access
Two-machine flowshop scheduling with flexible operations and controllable processing times
(2013) Uruk, Z.; Gultekin H.; Akturk, M. S.
We consider a two-machine flowshop scheduling problem with identical jobs. Each of these jobs has three operations, where the first operation must be performed on the first machine, the second operation must be performed on the second machine, and the third operation (named as flexible operation) can be performed on either machine but cannot be preempted. Highly flexible CNC machines are capable of performing different operations. Furthermore, the processing times on these machines can be changed easily in albeit of higher manufacturing cost by adjusting the machining parameters like the speed and/or feed rate of the machine. The overall problem is to determine the assignment of the flexible operations to the machines and processing times for each operation to minimize the total manufacturing cost and makespan simultaneously. For such a bicriteria problem, there is no unique optimum but a set of nondominated solutions. Using ε-constraint approach, the problem could be transformed to be minimizing total manufacturing cost for a given upper limit on the makespan. The resulting single criterion problem can be reformulated as a mixed integer nonlinear problem with a set of linear constraints. We use this formulation to optimally solve small instances of the problem while a heuristic procedure is constructed to solve larger instances in a reasonable time.