id: 05137717
dt: j
an: 05137717
au: Shadrokh, Shahram; Kianfar, Fereydoon
ti: A genetic algorithm for resource investment project scheduling problem,
    tardiness permitted with penalty.
so: Eur. J. Oper. Res. 181, No. 1, 86-101 (2007).
py: 2007
pu: Elsevier Science B.V.(North-Holland), Amsterdam
la: EN
cc: 
ut: project scheduling; genetic algorithms; resource; investment
ci: 
li: doi:10.1016/j.ejor.2006.03.056
ab: Summary: A genetic algorithm for solving a class of project scheduling
    problems, called Resource investment problem, is presented. Tardiness
    of project is permitted with defined penalty. Elements of algorithm
    such as chromosome structure, unfitness function, crossover, mutation,
    immigration and local search operations are explained. The performance
    of this genetic algorithm is compared with the performance of other
    published algorithms for resource investment problem. Also 690 problems
    are solved and their optimal solutions are used for the performance
    tests of the genetic algorithm. The tests results are quite
    satisfactory.
rv: