chapter two

2 A Deeper Look at Search and Optimization

 

This chapter covers

  • Classifying optimization problems based on different criteria.
  • Classifying search and optimization algorithms based on the way the search space is explored and how deterministic the algorithm is.
  • Introducing heuristics, meta-heuristics, and heuristic search strategies.
  • A first look at nature-inspired search and optimization algorithms.

2.1 Optimization Problem Classification

2.1.1 Number and Type of Decision Variables

2.1.2 Landscape and Number of Objective Functions

2.1.3 Constraints

2.1.4 Linearity of Objective Functions and Constraints

2.1.5 Expected Quality and Permissible Time of the Solution

2.2 Search and Optimization Algorithm Classification

2.3 Heuristics and Meta-heuristics

2.4 Nature-inspired Algorithms

2.5 Exercises

2.6 Summary