Scheduling with compressible and stochastic release dates

Authors:
Jian Zhang;Wensheng Yang;Yiliu Tu
Affiliations:
Department of Mechanical and Manufacturing Engineering, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Canada T2N 1N4;Management Science & Engineering, Nanjing University of Science & Technology, 200 Xiaolingwei Street, Nanjing, Jiangsu 210094, China;Department of Mechanical and Manufacturing Engineering, University of Calgary, 2500 University Drive NW, Calgary, Alberta, Canada T2N 1N4
Venue:
Computers and Operations Research
Year:
2013

Citing 10
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Abstract

In this work we study a one-machine scheduling problem which is featured by: (a) the release date of each job is compressible and stochastic, (b) each job has to be delivered before its due date (deadline) and (c) the manufacturer can expedite the production through overtime at an extra cost. The objective function of the scheduling problem is to minimize the total cost which includes the compressing cost and the overtime production cost. We propose a heuristic algorithm in which the stochastic problem is converted to the deterministic problem by a release-time ''converting policy''. We coin a concept of a job's late-release-impact factor (LRIF) and we propose a LRIF based converting policy. We compare the LRIF based converting policy with the ones used in practice, and the numerical test shows that the LRIF based converting policy can obtain the schedule with the lowest actual total cost.