In this paper a genetic algorithm (GA) is applied on Maximum
Betweennes Problem (MBP). The maximum of the objective function is
obtained by finding a permutation which satisfies a maximal number of
betweenness constraints. Every permutation considered is genetically coded
with an integer representation. Standard operators are used in the GA.
Instances in the experimental results are randomly generated. For smaller
dimensions, optimal solutions of MBP are obtained by total enumeration.
For those...

This research was partially supported by the Serbian Ministry of Science and Ecology under
project 144007. The authors are grateful to Ivana Ljubić for help in testing and to Vladimir Filipović for useful suggestions and comments.
In this paper a genetic algorithm (GA) for the task assignment
problem (TAP) is considered.An integer representation with standard genetic operators is used. Computational results are presented for instances
from the literature, and compared to optimal solutions...

In this paper a variable neighborhood search (VNS) approach
for the task assignment problem (TAP) is considered. An appropriate neighborhood
scheme along with a shaking operator and local search procedure
are constructed specifically for this problem. The computational results are
presented for the instances from the literature, and compared to optimal
solutions obtained by the CPLEX solver and heuristic solutions generated
by the genetic algorithm. It can be seen that the proposed VNS approach
reaches...

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