Optimization Algorithms

5 Simulated annealing

This chapter covers

• Introducing trajectory-based optimization algorithms
• Understanding the simulated annealing algorithm
• Solving function optimization as an example of continuous optimization problems
• Solving puzzle game problems like Sudoku as an example of constraint-satisfaction problems
• Solving permutation problems like TSP as an example of discrete problems
• Solving a real-world delivery semi-truck routing problem

In this chapter, we’ll look at simulated annealing as a trajectory-based metaheuristic optimization technique. We’ll discuss different elements of this algorithm and its adaptation aspects. A number of case studies will be presented to show the ability of this metaheuristic algorithm to solve continuous and ...