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Session 26 University of Southern California ISE514 Batch Processing and Batch Sequencing November 19, 2015 Geza P. Bottlik Page 1 Outline Questions? Project.

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Presentation on theme: "Session 26 University of Southern California ISE514 Batch Processing and Batch Sequencing November 19, 2015 Geza P. Bottlik Page 1 Outline Questions? Project."— Presentation transcript:

1 Session 26 University of Southern California ISE514 Batch Processing and Batch Sequencing November 19, 2015 Geza P. Bottlik Page 1 Outline Questions? Project simulation Short Quiz on 11/24 Overview of remaining topics (4 sessions)  Batch processing (1/2) 11/19  Batch Sequencing (1/2)11/19  Early Tardy (1/2)11/24  Sequence dependent setup (1/2)11/24  Net Present value (1/2)12/01  Stochastic problems(1/2)12/01  Review (1) 12/03

2 Session 26 University of Southern California ISE514 Batch Processing and Batch Sequencing November 19, 2015 Geza P. Bottlik Page 2 Batch Processing This is also called the baking problem A batch or baking problem is one where a single machine, the oven, processes more than one job at the same time The machine or oven has a limited capacity Processing in a batch machine is assumed to be uninterruptible - we cannot add or remove jobs once processing has started References: Baker 301, 313-321 (Skip Dynamic arrivals) D.R. Sule “Industrial Scheduling”, PWS Publishing, 1997 Morton and Pentico, pages 264- 266, 536 - 538

3 Session 26 University of Southern California ISE514 Batch Processing and Batch Sequencing November 19, 2015 Geza P. Bottlik Page 3 Batch Processing - heuristic - Tbar 1. Rank the jobs in ascending order of their arrival dates. Break ties with ascending order of due dates 2. Add an unscheduled job to a batch if: a. The job has arrived b. If it has the earliest due data of eligible jobs c. The batch is not full 3. The best solution has been obtained if a. Total tardiness is zero b. Each batch except the last one is filled and each has been started as early as possible

4 Session 26 University of Southern California ISE514 Batch Processing and Batch Sequencing November 19, 2015 Geza P. Bottlik Page 4 Batch Processing - heuristic - Tbar - continued 4. The solution may be improved by delaying a partially filled batch. Starting with the schedule that you evaluated in step 3: Starting with the first batch that is not full, check the effect of delays, one batch at a time. Repeat until no further improvement is possible

5 Session 26 University of Southern California ISE514 Batch Processing and Batch Sequencing November 19, 2015 Geza P. Bottlik Page 5 Batch sequencing Two parts belong to the same type if there is no set up required between the two parts Single machine problem - objective of meeting due dates and minimizing C max Heuristic: 1. Group the jobs by type, arrange in ascending order of due dates (can also try switching groups) 2. Calculate the minimum start time (MST) = Due date - (process +setup time) for each job 3. Place minimum MST first, calculate completion time

6 Session 26 University of Southern California ISE514 Batch Processing and Batch Sequencing November 19, 2015 Geza P. Bottlik Page 6 Batch sequencing - continued 4. Continue assigning jobs from the same group until either: a. all jobs in the group are assigned b. The total time exceeds the MST of a job in another group (designate it as job K) 5. If all jobs are assigned, stop. If not, remove the job that caused the MST to be exceeded and assign job K., if job K has a lower MST than the job to be displaced. Return to step 4


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