Browsing by Subject "Single machine scheduling"

Now showing 1 - 5 of 5

Open Access
Auction based scheduling for distributed systems
(International Institute of Informatics and Systemics, 2006) Zarifoğlu, Emrah; Sabuncuoğlu, İhsan
Businesses deal with huge databases over a geographically distributed supply network. When this is combined with scheduling and planning needs, it becomes too difficult to handle. Recently, Fast Consumer Goods sector tends to consolidate their manufacturing facilities on a single supplier serving to a distributed customer network. This decentralized structure causes imperfect information sharing between customers and the supplier. We model this problem as a single machine distributed scheduling problem with job agents representing the customers and the machine agent representing the supplier. We developed Auction Based Algorithm by exploiting the opportunity to use game theoretic approach to solve the problem in the decentralized utility case. Results of our extensive computational experiments indicate that Auction Based Algorithm converges to the upper bound found for the total utility measure.
Open Access
Generating robust and stable machine schedules from a proactive standpoint
(2009) Gören, Selçuk
In practice, scheduling systems are subject to considerable uncertainty in highly dynamic operating environments. The ability to cope with uncertainty in the scheduling process is becoming an increasingly important issue. In this thesis we take a proactive approach to generate robust and stable schedules for the environments with two sources of uncertainty: processing time variability and machine breakdowns. The information about the uncertainty is modeled using cumulative distribution functions and probability theory is utilized to derive inferences. We first focus on the single machine environment. We define two robustness (expected total flow time and expected total tardiness) and three stability (the sum of the squared and absolute differences of the job completion times and the sum of the variances of the realized completion times) measures. We identify special cases for which the measures can be optimized without much difficulty. We develop a dominance rule and two lower bounds for one of the robustness measures, which are employed in a branch-and-bound algorithm to solve the problem exactly. We also propose a beam-search heuristic to solve large problems for all five measures. We provide extensive discussion of our numerical results. Next, we study the problem of optimizing both robustness and stability simultaneously. We generate the set of all Pareto optimal points via -constraint method. We formulate the sub-problems required by the method and establish their computational complexity status. Two variants of the method that works with only a single type of sub-problem are also considered. A dominance rule and alternative ways to enforce the rule to strengthen one of these versions are discussed. The performance of the proposed technique is evaluated with an experimental study. An approach to limit the total number of generated points while keeping their spread uniform is also proposed. Finally, we consider the problem of generating stable schedules in a job shop environment with processing time variability and random machine breakdowns. The stability measure under consideration is the sum of the variances of the realized completion times. We show that the problem is not in the class NP. Hence, a surrogate stability measure is developed to manage the problem. This version of the problem is proven to be NP-hard even without machine breakdowns. Two branchand-bound algorithms are developed for this case. A beam-search and a tabu-search based two heuristic algorithms are developed to handle realistic size problems with machine breakdowns. The results of extensive computational experiments are also provided.
Open Access
Generating robust and stable schedules in a single machine environment
(IIE, 2004) Gören, Selçuk; Sabuncuoğlu, İhsan
Scheduling is a decision making process that concerns with allocation of limited resources (machines, material handling equipment, operators, tools, etc.) to competing tasks (operations of jobs) over time with the goal of optimizing one or more objectives. The output of this process is time/machine/operation assignments. In the scheduling theory, the objective is generally to optimize one or more regular performance measures such as makespan, flow-time, and tardiness. Recently, two new measures have been also used in scheduling applications: "robustness" and "stability". In this paper, we develop a new surrogate measure to achieve robustness and stability. This measure is embedded in a tabu search algorithm to generate schedules in a single machine environment subject to random machine breakdowns. The results of extensive computational experiments indicate that the proposed method performs better than the average slack method used in the literature.
Open Access
New insights on the single machine total tardiness problem
(Palgrave Macmillan, 1997) Tansel, B. C.; Sabuncuoğlu, İ.
Virtually all algorithmic studies on the single machine total tardiness problem use Emmons' theorems that establish precedence relations between job pairs. In this paper, we investigate these theorems with a geometric viewpoint. This approach provides a compact way of representing Emmons' theorems and promotes better insights into dominance properties. We use these insights to differentiate between certain classes of easy and hard instances.
Open Access
Single CNC machine scheduling with controllable processing times to minimize total weighted tardiness
(Elsevier, 2011) Akturk, M. S.; Ilhan, T.
Advanced manufacturing technologies, such as CNC machines, require significant investments, but also offer new capabilities to the manufacturers. One of the important capabilities of a CNC machine is the controllable processing times. By using this capability, the due date requirements of customers can be satisfied much more effectively. Processing times of the jobs on a CNC machine can be easily controlled via machining conditions such that they can be increased or decreased at the expense of tooling cost. Since scheduling decisions are very sensitive to the processing times, we solve the process planning and scheduling problems simultaneously. In this study, we consider the problem of scheduling a set of jobs on a single CNC machine to minimize the sum of total weighted tardiness, tooling and machining costs. We formulated the joint problem, which is NP-hard since the total weighted tardiness problem (with fixed processing times) is strongly NP-hard alone, as a nonlinear mixed integer program. We proposed a DP-based heuristic to solve the problem for a given sequence and designed a local search algorithm that uses it as a base heuristic.