TY - JOUR
T1 - Single machine scheduling to maximize the number of on-time jobs with generalized due-dates
AU - Gerstl, Enrique
AU - Mosheiov, Gur
N1 - Funding Information: This research was supported by the ISRAEL SCIENCE FOUNDATION (Grant No. 2505/19). The second author was also supported by the Charles I. Rosen Chair of Management and by The Recanati Fund of The School of Business Administration, The Hebrew University, Jerusalem, Israel. Publisher Copyright: © 2020, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2020/6/1
Y1 - 2020/6/1
N2 - In scheduling problems with generalized due dates (gdd), the due dates are specified according to their position in the sequence, and the j-th due date is assigned to the job in the j-th position. We study a single-machine problem with generalized due dates, where the objective is maximizing the number of jobs completed exactly on time. We prove that the problem is NP-hard in the strong sense. To our knowledge, this is the only example of a scheduling problem where the job-specific version has a polynomial-time solution, and the gdd version is strongly NP-hard. A branch-and-bound (B&B) algorithm, an integer programming (IP)-based procedure, and an efficient heuristic are introduced and tested. Both the B&B algorithm and the IP-based solution procedure can solve most medium-sized problems in a reasonable computational effort. The heuristic serves as the initial step of the B&B algorithm and in itself obtains the optimum in most cases. We also study two special cases: max-on-time for a given job sequence and max-on-time with unit-execution-time jobs. For both cases, polynomial-time dynamic programming algorithms are introduced, and large-sized problems are easily solved.
AB - In scheduling problems with generalized due dates (gdd), the due dates are specified according to their position in the sequence, and the j-th due date is assigned to the job in the j-th position. We study a single-machine problem with generalized due dates, where the objective is maximizing the number of jobs completed exactly on time. We prove that the problem is NP-hard in the strong sense. To our knowledge, this is the only example of a scheduling problem where the job-specific version has a polynomial-time solution, and the gdd version is strongly NP-hard. A branch-and-bound (B&B) algorithm, an integer programming (IP)-based procedure, and an efficient heuristic are introduced and tested. Both the B&B algorithm and the IP-based solution procedure can solve most medium-sized problems in a reasonable computational effort. The heuristic serves as the initial step of the B&B algorithm and in itself obtains the optimum in most cases. We also study two special cases: max-on-time for a given job sequence and max-on-time with unit-execution-time jobs. For both cases, polynomial-time dynamic programming algorithms are introduced, and large-sized problems are easily solved.
KW - Branch-and-bound algorithm
KW - Generalized due dates
KW - Heuristic
KW - NP-hardness
KW - Scheduling
KW - Single machine
UR - http://www.scopus.com/inward/record.url?scp=85080925413&partnerID=8YFLogxK
U2 - https://doi.org/10.1007/s10951-020-00638-7
DO - https://doi.org/10.1007/s10951-020-00638-7
M3 - Article
SN - 1094-6136
VL - 23
SP - 289
EP - 299
JO - Journal of Scheduling
JF - Journal of Scheduling
IS - 3
ER -