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Stochastic Scheduling in Single Machine and Flow Shop Environments

Elyasi, Ali | 2012

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  1. Type of Document: Ph.D. Dissertation
  2. Language: Farsi
  3. Document No: 43907 (01)
  4. University: Sharif University of Technology
  5. Department: Industrial Engineering
  6. Advisor(s): Salmasi, Naser
  7. Abstract:
  8. Sequencing and scheduling of jobs are decision making processes that are used in many manufacturing and service industries. In the traditional scheduling models, it is assumed that the values for all the problem parameters are constant and known in advance. However, production environments in the real world are subject to many sources of uncertainty or randomness. This research investigates three different types of stochastic scheduling problems. In the first case, the problem is minimizing the number of tardy jobs in the class of static list policies, where the job processing times are random variables. For this case, the stochastic problems in single machine and flow shop environments are modeled and solved using chance constrained programming. It is shown that the stochastic problems featuring special cases of processing times are as easy as their deterministic counterparts. In the second case, the problem is minimizing the number of tardy jobs in the class of dynamic policies, where the job due dates are random variables. For this case, a dynamic scheduling method is proposed to solve the problem in a flow shop environment. Computational study validates the effectiveness of the proposed method. In the third case, the job due dates are decision variables. Thus, in addition to job sequence, the optimal due date for each job should be determined. For this case, two different problems are studied in a single machine environment where the job processing times are random variables. The first problem is to minimize the maximum due date so that all jobs are on time. A simple method is developed to solve this problem. The other problem is to minimize a total cost function which is a linear combination of three penalties: penalty on job earliness, penalty on job tardiness, and penalty associated with long due date assignment. It is shown that the optimal sequence for the case of common due date is V-shaped
  9. Keywords:
  10. Flow Shop Scheduling ; Due Date Assignment ; Stochastic Scheduling ; Single Machine ; Tardy Jobs ; Chance Constrained Programming ; Dynamic Scheduling

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