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Pix4dmapper scale constraints
Pix4dmapper scale constraints








In: Desaulniers G, Desrosiers J, Solomon MM (eds) Column Generation, chap. Springer, New Yorkĭesrosiers J, Lübbecke M (2005b) A primer in column generation. Elsevier, Amsterdam, pp 35–139ĭesaulniers G, Desrosiers J, Solomon MM (eds) (2005a) Column generation. In: Ball M et al (eds) Network Routing, Handbooks in Operations Research and Management Science, vol 8. In: Crainic TG, Laporte G (eds) Fleet Management and Logistics, Norwell, pp 57–93ĭesrosiers J, Dumas Y, Solomon MM, Soumis F (1995a) Time constrained routing and scheduling. European J Oper Res 97:245–259ĭesaulniers G, Desrosiers J, Ioachim I, Solomon MM, Soumis F, Villeneuve D (1998) A unified framework for deterministic time constrained vehicle routing and crew scheduling problems. European J Oper Res 97:260–268ĭesaulniers G, Desrosiers J, Dumas Y, Marc S, Rioux B, Solomon MM, Soumis F. European J Oper Res 262:835–850Ĭhu HD, Gelman E, Johnson EL (1997) Solving large scale crew scheduling problems. Oper Res 46:316–329īouarab H, El Hallaoui I, Metrane A, Soumis F (2017) Dynamic constraint and variable aggregation in column generation.

pix4dmapper scale constraints

Transp Sci 32(3):221–231īarnhart C, Johnson EL, Nemhauser GL, Savelsbergh MWP, Vance PH (1998b) Branch-and-price: column generation for solving huge integer programs.

pix4dmapper scale constraints

Comput Oper Res 36(4):1284–1298īarnhart C, Shenoi R (1998a) An approximate model and solution approach for the long-haul crew pairing problem. Our computational results show, first, the potential gains that can be obtained by using wider time windows and, second, the very good performance of the proposed algorithm when compared with a standard CG/RH algorithm for solving an industrial monthly CPP instance with 46,588 flights.ĪhmadBeygi S, Cohn A, Weir M (2009) An integer programming approach to generating airline crew pairings. When embedded in a rolling-horizon (RH) procedure, DCA allows to consider wider time windows in RH and yields better solutions. This algorithm combines, among others, column generation (CG) with dynamic constraint aggregation (DCA) that can efficiently exploit the CG master problem degeneracy.

pix4dmapper scale constraints

In this paper, we propose an effective algorithm for solving very large-scale CPP instances. Only a few papers have addressed monthly instances with up to 14,000 flights. This problem has been widely studied but most works have tackled daily or weekly CPP instances with up to 3500 flights.

pix4dmapper scale constraints

The monthly crew pairing problem (CPP) consists of determining a least-cost set of feasible crew pairings (sequences of flights starting and ending at a crew base) such that each flight is covered once and side constraints are satisfied.










Pix4dmapper scale constraints