Browsing by Subject "Job Shop Scheduling"
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Item Open Access Analysis of reactive scheduling problems in manufacturing systems(Bilkent University, 1997) Bayız, MuratIn this study we develop a new scheduling algorithm for the job shop problem. The proposed algorithm is a heuristic method based on the filtered beam search. After extensive analyses on the evaluation functions and search parameters of the beam search, we measure the performance of the algorithm in terms of quality of solutions and CPU times for both the makespan and mean tardiness criteria. In the second half of the research, we study the reactive scheduling problem. Specifically, we analyze several reactive methods such as no response, periodic response and continuous response under various experimental conditions. The beam search based partial scheduling is also studied in this thesis. The method is analyzed for both deterministic and stochastic environments under several job shop configurations.Item Open Access Flowtime estimation in dynamic job shops(Bilkent University, 1996) Çömlekçi, AbdullahIn the scheduling literature, estimation of job flowtimes has always been an important issue since the late sixties. The previous studies focus on the problem in the context of due date assignment and develop methods using aggregate information in the estimation process. In this study, we propose a new method which utilizes the job, shop and route information on an operational basis. The performance of the proposed method is measured using a simulation model. It is also compared with the existing methods for a wide variety of performance measures under various experimental conditions.Item Open Access A learning-based schedulıng system wıth continuous control and update structure(Bilkent University, 2005) Metan, GökhanIn today’s highly competitive business environment, the product varieties of firms tend to increase and the demand patterns of commodities change rapidly. Especially for high tech industries, the product life cycles become very short and the customer demand can change drastically due to the introduction of new technologies in the market (i.e., introduction by the competitors). These factors increase the need for more efficient scheduling strategies. In this thesis, a learning-based scheduling system for a classical job shop problem with the average tardiness objective is developed. The system learns on the manufacturing environment by constructing a learning tree and selects a dispatching rule from the tree for each scheduling period to schedule the operations. The system also utilizes the process control charts to monitor the performance of the learning tree and the tree as well as the control charts is updated when necessary. Therefore, the system adapts itself for the changes in the manufacturing environment and survives in time. Also, extensive simulation experiments are performed for the system parameters such as monitoring (MPL) and scheduling period lengths (SPL). Our results indicate that the system performance is significantly affected by the parameters (i.e., MPL and SPL). Moreover, simulation results show that the performance of the proposed system is considerably better than the simulation-based single-pass and multi-pass scheduling algorithms available in the literatureItem Open Access A re-examination of the effectiveness of priority rules in a dynamic job shop environment(Bilkent University, 1997) Lejmi, TaharIII dyiiaiuic job .shop .sdiccliiliiig li(cra(urc, an cxicnsivc research clioil lias been spent to study the performance of priority rules, wliich play an important role to manage scheduling tasks in real life manufacturing systems. This study extends the previous research on priority rules by investigating the effect of due date, processing time, and load variation on the pei (drmance of some well used priority rules in a Job shop environment. Furthermore, tliis study will analyze the performance of the rules under the due window approach. The performance of the rules will be measured in terms of two regular criteria: mean flow time and mean tardiness. In addition, with the incieasing emphasis on using non regular measures, we further study the performance of the rules with respect to the mean absolute deviation (MAD) criterion. Finally, we propose two new rules that perform quiet effectively for the MAD criterion.