 Heuristics for Solving the Crew Rostering ProblemLin Xie ()
Chapter 7 in Decision Support for Crew Rostering in Public Transit, 2015, pp 67-106 from Springer Abstract: Abstract As shown in Chapter 6, some instances can not be solved optimally within 24 hours with solvers or are unsolvable due to a shortage of memory (especially with the integrated approach). Therefore, in this chapter we try to develop some heuristics to identify good solutions to the crew rostering problem. We begin this chapter with some information in Section 7.1 shared by the heuristics, i.e. update of meta-information, local search operators, and generation of an initial solution. In Section 7.2, different metaheuristics are developed to solve the rota scheduling problem of the NCCR problem. The best metaheuristic is chosen to solve the integrated problem of the NCCR and CCR problems in Section 7.3. Column generation approaches for the rota scheduling problem, and for the integrated problem of both NCCR and CCR problems, are then described in Sections 7.4.1 and 7.4.2. Next, a multi-objective metaheuristic is described in Section 7.5. Finally, the experimental results are shown in Section 7.6. The notation used in this chapter, including the sets, parameters, and variables, is the same as in Chapter 5. Date: 2015 There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it. Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-658-08167-6_7 Ordering information: This item can be ordered from DOI: 10.1007/978-3-658-08167-6_7 Access Statistics for this chapter More chapters in Springer Books from Springer |
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