Define alternatives to the Tietz and Bart heuristic
Outline the Tietz and Bart interchange heuristic
Describe the process whereby an element within a random solution is exchanged, and if it improves the solution, it is accepted, and if not, it is rejected and another element is tried until no improvement occurs in the objective function value
Demonstrate how to implement a greedy heuristic process
Identify problems for which the greedy heuristic also produces the optimal solution (e.g., Kruskal’s algorithm for minimum spanning tree, the fractional Knapsack problem)
Define alternatives to the Tietz and Bart heuristic
Outline the Tietz and Bart interchange heuristic
Describe the process whereby an element within a random solution is exchanged, and if it improves the solution, it is accepted, and if not, it is rejected and another element is tried until no improvement occurs in the objective function value
Demonstrate how to implement a greedy heuristic process
Identify problems for which the greedy heuristic also produces the optimal solution (e.g., Kruskal’s algorithm for minimum spanning tree, the fractional Knapsack problem)
AM-76 - Simulated annealing