Accelerated tabu search for no-wait flowshop scheduling problem with maximum lateness criterion

Chuyang Wang, Xiaoping Li and Qian Wang

European Journal of Operational Research, 2010, vol. 206, issue 1, 64-72

Abstract: For the no-wait flowshop scheduling problem with maximum lateness criterion, properties are developed to speed up three kinds of basic operations generating candidate solutions, i.e., the insertion of a new job into a partial sequence, and the insertion and exchange neighborhood moves. The properties reduce the time to evaluate a candidate from O(nm) to O(1) and simplify the implementation of the heuristics based on the basic operations by evaluating candidates before their generation. The properties also reduce from O(n3m) to O(n2) the time complexity of well-known NEH heuristic and the complete evaluation of the insertion and exchange neighborhoods. Tabu search (TS) is applied to the considered problem, since TS tries to find the best neighbor of the current solution in each iteration and therefore can much benefit from the speedups. Three different ways to use insertion and exchange neighborhoods are compared in TS. Computational experiments show that the speedups are more helpful as job number increases and all proposed TS algorithms are more effective and robust than the existing algorithms. Although two- and single-neighborhood TS algorithms are not significantly different, two-neighborhood TS algorithms are more preferable.

Keywords: Scheduling; No-wait; flowshop; Maximum; lateness; Tabu; search; Neighborhood (search for similar items in EconPapers)
Date: 2010
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0377-2217(10)00119-0
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:206:y:2010:i:1:p:64-72

Access Statistics for this article

European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

More articles in European Journal of Operational Research from Elsevier
Bibliographic data for series maintained by Catherine Liu ().