Fundamentals of Computational Swarm Intelligence Book

1	Introduction	1
2	Optimization problems and methods	7
3	Unconstrained optimization	19
4	Constrained optimization	27
5	Multi-solution problems	37
6	Multi-objective optimization	41
7	Dynamic optimization problems	49
8	Introduction to evolutionary computation	57
9	Evolutionary computation paradigms	67
10	Coevolution	79
11	Introduction	87
12	Basic particles swarm optimization	93
13	Particle trajectories	131
14	Convergence proofs	161
15	Single-solution particle swarm optimization	177
16	Niching with particle swarm optimization	223
17	Constrained optimization using particle swarm optimization	251
18	Multi-objective optimization with particle swarms	271
19	Dynamic environments with particle swarm optimization	317
20	Discrete particle swarm optimization	329
21	Particle swarm optimization applications	345
22	Introduction	363
23	Ant colony optimization meta-heuristic	367
24	General frameworks for ant colony optimization algorithms	397
25	Ant colony optimization algorithms	409
26	Ant colony optimization applications	447
27	Collective decision-making	479
28	Ant colony optimization convergence	487
29	Cometery organization and brood care	493
30	Division of labor	505
31	Final remarks	511