fitness.fun: Fitness function for our dynamic VRP approach.
In jakobbossek/dynvrp: EMOA for a dynamic Orienteering Problem
Description
Usage
Arguments
Value
Description
We aim to minimize the tour length and the number of
unvisited customers with later requests in time. Note: tour
length depends not only on the edge costs, i.e., driving from
customer i to j, but on the release dates of j too. So given a tour
t1,t2,...,tk we end up with the following recursive formulation
f(t1,tj) = max(f(t1,t(j-1)), r[j]) + d[i, j].
Usage
1
fitness.fun(ind, instance)
Arguments
ind
[VRPIndividual]
Encoding of individual.
instance
[Network]
Network instance.
Value
[numeric(2)] Vector of tour length and number of
unvisited dynamic customers.
jakobbossek/dynvrp documentation built on Jan. 19, 2020, 9:53 p.m.
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Description Usage Arguments Value
Description
We aim to minimize the tour length and the number of unvisited customers with later requests in time. Note: tour length depends not only on the edge costs, i.e., driving from customer i to j, but on the release dates of j too. So given a tour t1,t2,...,tk we end up with the following recursive formulation f(t1,tj) = max(f(t1,t(j-1)), r[j]) + d[i, j].
Usage
1 | fitness.fun(ind, instance)
|
Arguments
ind |
[ |
instance |
[ |
Value
[numeric(2)] Vector of tour length and number of
unvisited dynamic customers.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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