Meta-heuristic and Evolutionary Algorithms for Engineering Optimization

List of Figures

Figure 1.1	Decision space of a constrained two‐dimensional optimization problem.
Figure 1.2	Schematic of global and local optimums in a one‐dimensional maximizing optimization problem.
Figure 1.3	Different types of decision spaces: (a) maximization problem with single‐modal surface and one global optimum; (b) maximization problem with multimodal surface that has one global optimum.
Figure 1.4	Demonstration of near optima in a one‐dimensional maximizing optimization problem.
Figure 1.5	Compound gear train made of four gears.
Figure 1.6	Schematic of a two‐bar truss.
Figure 1.7	Schematic of a hydropower dam.
Figure 2.1	Sampling grid on a two‐dimensional decision space.
Figure 2.2	General schematic of a simple algorithm; K denotes the counter of iterations.
Figure 2.3	Diagram depicting the relation between a simulation model and an optimization algorithm.
Figure 2.4	The main components of the optimization by meta‐heuristic and evolutionary algorithms.
Figure 2.5	Different solutions in a two‐dimensional decision space.
Figure 2.6	Selection probability of a set of solutions 1–10 of a hypothetical maximization problem.
Figure 2.7	The flowchart of the general algorithm.
Figure 2.8	Convergence history of an optimization algorithm toward the best solution in a minimization problem.
Figure 2.9	Convergence of an optimization algorithm in which the best solution is not always transferred to the next iteration during the search in a minimization ...