public class SchrimpfAcceptance extends Object implements SolutionAcceptor, IterationStartsListener, AlgorithmStartsListener
The idea can be described as follows: Most problems do not only have one unique minimum (maximum) but
a number of local minima (maxima). To avoid to get stuck in a local minimum at the beginning of a search
this threshold-acceptance function accepts also worse solution at the beginning (in contrary to a greedy
approach which only accepts better solutions), and converges to a greedy approach at the end.
The difficulty is to define (i) an appropriate initial threshold and (ii) a corresponding function describing
how the threshold converges to zero, i.e. the greedy threshold.
ad i) The initial threshold is determined by a random walk through the search space. The random walk currently runs with the following algorithm: src/main/resources/randomWalk.xml. It runs as long as it is specified in nuOfWarmupIterations. In the first iteration or walk respectively the algorithm generates a solution. This solution in turn is the basis of the next walk yielding to another solution value ... and so on. Each solution value is memorized since the initial threshold is essentially a function of the standard deviation of these solution values. To be more precise: initial threshold = stddev(solution values) / 2.
ad ii) The threshold of iteration i is determined as follows: threshold(i) = initialThreshold * Math.exp(-Math.log(2) * (i / nuOfTotalIterations) / alpha) To get a better understanding of the threshold-function go to Wolfram Alpha and plot the following line (just copy and paste it into Wolfram's console: www.wolframalpha.com):
100. * exp(-log(2)* (x/1000) / 0.1) (x from 0 to 1000) (y from 0 to 100)
with
initialThreshold = 100
nuOfTotalIter = 1000
alpha = 0.1
x corresponds to i iterations and
y to the threshold(i)
Gerhard Schrimpf, Johannes Schneider, Hermann Stamm- Wilbrandt, and Gunter Dueck (2000). Record breaking optimization results using the ruin and recreate principle. Journal of Computational Physics, 159(2):139 – 171, 2000. ISSN 0021-9991. doi: 10.1006/jcph.1999. 6413. URL http://www.sciencedirect.com/science/article/ pii/S0021999199964136
| Constructor and Description |
|---|
SchrimpfAcceptance(int solutionMemory,
double alpha) |
| Modifier and Type | Method and Description |
|---|---|
boolean |
acceptSolution(Collection<VehicleRoutingProblemSolution> solutions,
VehicleRoutingProblemSolution newSolution)
Accepts solution or not, and returns true if a new solution has been accepted.
|
double |
getInitialThreshold() |
void |
informAlgorithmStarts(VehicleRoutingProblem problem,
VehicleRoutingAlgorithm algorithm,
Collection<VehicleRoutingProblemSolution> solutions) |
void |
informIterationStarts(int i,
VehicleRoutingProblem problem,
Collection<VehicleRoutingProblemSolution> solutions) |
void |
setInitialThreshold(double initialThreshold)
Sets initial threshold.
|
String |
toString() |
public boolean acceptSolution(Collection<VehicleRoutingProblemSolution> solutions, VehicleRoutingProblemSolution newSolution)
SolutionAcceptor
If the solution is accepted, it is added to solutions, i.e. the solutions-collections is modified.
acceptSolution in interface SolutionAcceptorsolutions - collection of existing solutionsnewSolution - new solution to be evaluatedpublic double getInitialThreshold()
public void setInitialThreshold(double initialThreshold)
Note that if initial threshold has been set, automatic generation of initial threshold is disabled.
initialThreshold - the initialThreshold to setpublic void informAlgorithmStarts(VehicleRoutingProblem problem, VehicleRoutingAlgorithm algorithm, Collection<VehicleRoutingProblemSolution> solutions)
informAlgorithmStarts in interface AlgorithmStartsListenerpublic void informIterationStarts(int i,
VehicleRoutingProblem problem,
Collection<VehicleRoutingProblemSolution> solutions)
informIterationStarts in interface IterationStartsListenerCopyright © 2013–2016. All rights reserved.