Advertisement

Planning personnel retraining: column generation heuristics

Article

Abstract

Retraining of staff is a compulsory managerial function in many organisations and often requires planning for a large number of employees. The large scale of this problem and various restrictions on the resultant assignment to classes make this planning challenging. The paper presents a complexity analysis of this problem together with linear and nonlinear mathematical programming formulations. Three different column generation based optimisation procedures and a large neighbourhood search procedure, incorporating column generation, are compared by means of computational experiments. The experiments used data typical to large electricity distributors.

Keywords

Personnel retraining Column generation Integer programming Heuristic Large neighbourhood search 

References

  1. Blte A, Thonemann UW (1996) Optimizing simulated annealing schedules with genetic programming. Eur J Oper Res 92(2):402–416.  https://doi.org/10.1016/0377-2217(94)00350-5. http://www.sciencedirect.com/science/article/pii/0377221794003505
  2. Caprara A, Pisinger D, Toth P (1999) Exact solution of the quadratic knapsack problem. INFORMS J Comput 11(2):125–137MathSciNetCrossRefMATHGoogle Scholar
  3. Chen Y, Hao JK (2015) Iterated responsive threshold search for the quadratic multiple knapsack problem. Ann Oper Res 226:101–131MathSciNetCrossRefMATHGoogle Scholar
  4. Chen Y, Hao JK, Glover F (2016) An evolutionary path relinking approach for the quadratic multiple knapsack problem. Knowl Based Syst 92:23–34CrossRefGoogle Scholar
  5. Chopra S, Rao MR (1993) The partition problem. Math Program 59(1–3):87–115CrossRefMATHGoogle Scholar
  6. Cornuéjols G, Nemhauser GL, Wolsey LA (1983) The uncapacitated facility location problem. Carnegie-mellon univ pittsburgh pa management sciences research group, Tech. repGoogle Scholar
  7. Desrosiers J, Lübbecke ME (2005) A primer in column generation. Springer, BerlinCrossRefMATHGoogle Scholar
  8. Drezner Z (2003) A new genetic algorithm for the quadratic assignment problem. INFORMS J Comput 15(3):320–330.  https://doi.org/10.1287/ijoc.15.3.320.16076. MathSciNetCrossRefMATHGoogle Scholar
  9. García-Martínez C, Rodriguez F, Lozano M (2014) Tabu-enhanced iterated greedy algorithm: a case study in the quadratic multiple knapsack problem. Eur J Oper Res 232:454–463MathSciNetCrossRefMATHGoogle Scholar
  10. Garey MR, Johnson DS (1979) Computers and intractability: a guide to np-completeness. Freeman, San FranciscoMATHGoogle Scholar
  11. Gintner V, Kliewer N, Suhl L (2005) Solving large multiple-depot multiple-vehicle-type bus scheduling problems in practice. OR Spectr. 27(4):507–523CrossRefMATHGoogle Scholar
  12. Goldschmidt O, Hochbaum DS, Levin A, Olinick EV (2003) The sonet edge-partition problem. Networks 41(1):13–23MathSciNetCrossRefMATHGoogle Scholar
  13. Hiley A, Julstrom BA (2006) The quadratic multiple knapsack problem and three heuristic approaches to it. In: Proceedings of the 8th annual conference on genetic and evolutionary computation. ACM, pp 547–552Google Scholar
  14. Johnson EL, Mehrotra A, Nemhauser GL (1993) Min-cut clustering. Math program 62(1–3):133–151MathSciNetCrossRefMATHGoogle Scholar
  15. Julstrom BA (2005) Greedy, genetic, and greedy genetic algorithms for the quadratic knapsack problem. In: Proceedings of the 7th annual conference on genetic and evolutionary computation. ACM, pp 607–614Google Scholar
  16. Pisinger D, Ropke S (2010) Large neighborhood search. In: Potvin J-Y, Gendreau M (eds) Handbook of metaheuristics. Springer, Boston, pp 399–419CrossRefGoogle Scholar
  17. Pochet Y, Wolsey LA (2006) Production planning by mixed integer programming. Springer, BerlinMATHGoogle Scholar
  18. Shaw P (1998) Using constraint programming and local search methods to solve vehicle routing problems. In: International conference on principles and practice of constraint programming. Springer, pp 417–431Google Scholar
  19. Taşkın ZC, Smith JC, Ahmed S, Schaefer AJ (2009) Cutting plane algorithms for solving a stochastic edge-partition problem. Discrete Optim 6(4):420–435MathSciNetCrossRefMATHGoogle Scholar
  20. Wang H, Kochenberger G, Glover F (2012) A computational study on the quadratic knapsack problem with multiple constraints. Comput Oper Res 39(1):3–11MathSciNetCrossRefMATHGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of Mathematical SciencesUniversity of Technology SydneyUltimoAustralia

Personalised recommendations