Stochastic scheduling to minimize expected maximum lateness | Macquarie University ResearchOnline

Home

List Of Titles

Stochastic scheduling to minimize expected maximum lateness

Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.14/75091

51 Visitors

67 Hits

4 Downloads

Title: Stochastic scheduling to minimize expected maximum lateness
Related: European journal of operational research, Vol. 190, Issue 1, p.103-115
DOI: 10.1016/j.ejor.2007.06.015
Publisher: Elsevier
Date: 2008
FoR/RFCD Code(s): 010000 Mathematical Sciences 080000 Information And Computing Sciences 090000 Engineering
Author/Creator: Wu, Xianyi
Author/Creator: Zhou, Xian
Description: This paper is concerned with the problems in scheduling a set of jobs associated with random due dates on a single machine so as to minimize the expected maximum lateness in stochastic environment. This is a difficult problem and few efforts have been reported on its solution in the literature. In this paper, we first derive a deterministic equivalent to the expected maximum lateness and then propose a dynamic programming algorithm to obtain the optimal solutions. The procedures to compute optimal solutions are initially developed in the case of deterministic processing times, and then extended to stochastic processing times following arbitrary probability distributions. Moreover, several heuristic rules are suggested to compute near-optimal solutions, which are shown to be highly efficient and accurate by computer-based experiments.
Description: 13 page(s)
Subject Keyword: 010000 Mathematical Sciences
Subject Keyword: 080000 Information And Computing Sciences
Subject Keyword: 090000 Engineering
Subject Keyword: stochastic scheduling
Subject Keyword: due dates
Subject Keyword: expected maximum lateness
Subject Keyword: dynamic programming algorithms
Resource Type: journal article
Organisation: Macquarie University. Dept. of Actuarial Studies

Identifier: http://hdl.handle.net/1959.14/75091
Identifier: ISSN:0377-2217
Identifier: mq-rm-2007006966
Language: eng
Reviewed

Macquarie University ResearchOnline

Search

Browse

Highlights

Resources