The Research on Web-Based Testing Environment Using Simulated Annealing Algorithm

Algorithm 1

Java code description of the algorithm.

public  int GetNextIdByF(int studentId, String testTime, double cita) throws SQLException {

  ProblemControl pc = new ProblemControl();

  int IDMAX = 691;

  double  𝐾 = 20.00;

  int  𝑘 = 0;

  // Cooling parameter table

  int MarkovLength = 25;

  double Temperature = 100;

  double Tolerance = 1𝑒−5;

  int PreId, NextId;

  int BestId; // Optimal solution

  Random random = new Random();

  PreId = pc.GetRandomProblemId();

  BestId = PreId;

  do  {

    Temperature = (𝐾−𝑘)∗5;

     𝑘++;

     for (int  𝑖 = 0; 𝑖 < MarkovLength; 𝑖++) {

    // (1) Selected solutions from the neighborhood structure

    do  {

      NextId = pc.GetRandomProblemId();

       if  (NextId == PreId) {

      NextId = pc.GetRandomProblemId();

        }

     }  while (!(NextId ≥ 0 && NextId ≤ IDMAX));

   // (2) Whether the global optimum solution?

      if  (pc.ObjectFunction(studentId, testTime, BestId, cita)

       ≤ pc.ObjectFunction(studentId, testTime, NextId, cita)) {

       PreBestId = BestId; // retain the previous Optimal solution

       BestId = NextId; //the new optimal solution;

      }

   // (3) Metropolis process

      if  (pc.ObjectFunction(studentId, testTime, PreId, cita)

       − pc.ObjectFunction(studentId, testTime, NextId, cita) < 0) {

        PreId = NextId;

      }  else  {

        double change = −1 * (pc.ObjectFunction(studentId, testTime, PreId, cita)

                  − pc.ObjectFunction(studentId, testTime, NextId, cita)) / Temperature;

       if  (Math.exp(change) > random.nextDouble()) {

        PreId = NextId;

       }  else  {

         Not accepted, save the original solution

     }

      }

   } //According to Metropolis acceptance criteria to judge

   }

   while  (Math.abs(pc.ObjectFunction(studentId, testTime, BestId, cita)

         − pc.ObjectFunction(studentId, testTime, PreBestId, cita))

         > Tolerance && Temperature ≥ 0); // Termination condition

  return BestId; // Return to the optimal solution

 }