knapsack::knapsack(const knapsack &k)
// Knapsack copy constructor
{
numObjects = k.getNumObjects();
costBound = k.getCostBound();
value.resize(numObjects);
cost.resize(numObjects);
index.resize(numObjects);
selected.resize(numObjects);
for (int i = 0; i < numObjects; i++)
{
setValue(i,k.getValue(i));
setCost(i,k.getCost(i));
setIndex(i,k.getIndex(i));
if (k.isSelected(i))
select(i);
else
unSelect(i);
}
setNum(k.getNum());
currentValue = k.getCurrentValue();
currentCost = k.getCurrentCost();
}
knapsack greedyKnapsack(vector<pair<double,int>> sortedSack, knapsack sack)
{
int sackIndex;
// outer for loop is iterating through sortedSack ratios
// look for highest ratio item
for (int i = 0; i < sack.getNumObjects(); i++)
{
// use second value of sorted sack pair as index
sackIndex = sortedSack.at(i).second;
//get ratio for specific sack(sackIndex)
double ratioKnap;
double valKnap = sack.getValue(sackIndex);
double costKnap = sack.getCost(sackIndex);
ratioKnap = valKnap / costKnap;
if (sack.getCost() + sack.getCost(sackIndex) <= sack.getCostLimit())
{
sack.select(sackIndex);
}
}
for (int k = 0; k < sack.getNumObjects(); k++)
{
cout<<sack.isSelected(k)<<endl;
}
return sack;
}
void exhaustiveKnapsack(knapsack sack, int timeLimit)
{
// Get start time to be used in while loop
time_t startTime;
time(&startTime);
// a while loop that expires when time limit is complete by checking difference of
// start time and current time at every loop
while (true)
{
// Get current time and stop when greater than input time limit
time_t newTime;
time(&newTime);
if (difftime(newTime, startTime) > timeLimit)
{
cout << "Time limit expired";
break;
}
// Put main code here
// Update current weight in sack every iteration of while loop
int itemsSelected = 0;
int currentWeight = 0;
for (int i = 0; i < sack.getNumObjects(); i++)
{
itemsSelected++;
currentWeight = sack.getCost(i) + currentWeight;
}
// Create random index to put into sack
srand(time(NULL));
int randNum = rand() % sack.getNumObjects();
// if item isn't selected, and there is enough space, then select item
if ((sack.isSelected(randNum) == false) && sack.getCost(randNum) + currentWeight <= sack.getCostLimit())
{
sack.select(randNum);
}
// Need an exit case where there is no more items that can fit in the sack
else if (sack.getCost(randNum) + currentWeight > sack.getCostLimit())
{
// need to record sack weight and value and items when this happens (and there are
// no more items that can legally be added)
}
}
}
void printSolution(knapsack &k, string filename)
// Prints out the solution.
{
ofstream myfile;
myfile.open (filename.c_str());
myfile << "------------------------------------------------" << endl;
myfile << "Total value: " << k.getCurrentValue() << endl;
myfile << "Total cost: " << k.getCurrentCost() << endl << endl;
// Print out objects in the solution
for (int i = 0; i < k.getNumObjects(); i++)
if (k.isSelected(i))
myfile << i << " " << k.getValue(i) << " " << k.getCost(i) << endl;
myfile << endl;
myfile.close();
}
/**
* Finds a local optimum and returns the result
*
* @param k knapsack to find local optimum for
* @param int 2-opt or 3-opt
* @return new knapsack with a local opt solution
*/
knapsack localOptimum(knapsack &k, int opt)
{
knapsack original(k);
deque<knapsack> problem;
knapsack bestFound = knapsack(k);
try
{
for (int l = 0; l < k.getNumObjects() - 1; l++)
{
k = knapsack(original);
if (!k.isSelected(l))
continue;
k.unSelect(l);
for (int m = l; m < k.getNumObjects() - 1; m++)
{
if (!k.isSelected(m))
continue;
k.unSelect(m);
if (opt == 3)
{
for (int n = m; n < k.getNumObjects() - 1; n++)
{
if (!k.isSelected(n))
continue;
k.unSelect(n);
problem.push_front(knapsack(k));
}
}
else
problem.push_front(knapsack(k));
}
}
while(problem.size() > 0)
{
checkTimeLimit();
knapsack current = problem.front();
problem.pop_front();
deque<knapsack> solution;
solution.push_front(knapsack(current));
int currentIndex = 0;
while(solution.size() > 0)
{
knapsack currentSolution = solution.front();
solution.pop_front();
if (currentSolution.getValue() > bestFound.getValue())
{
bestFound = knapsack(currentSolution);
}
if (currentIndex < currentSolution.getNumObjects() - 1)
{
if (!currentSolution.isSelected(currentIndex) &&
(currentSolution.getCost() + currentSolution.getCost(currentIndex)) < currentSolution.getCostLimit())
{
currentSolution.select(currentIndex);
solution.push_front(knapsack(currentSolution));
}
currentIndex++;
}
}
}
return bestFound;
}
catch (baseException &ex)
{
cout << ex.what() << endl;
return bestFound;
}
} //end localOptimum
