Simulated annealing, genetic algorithms, evolutionary programming, swarm intelligence, and ant colony optimization are active research areas in Smart and intelligent innovative algorithms. In particular, Particle Swarm Intelligence (PSI) attracts more attentions because of its simplicity and time efficiency. Recent advance on PSI research includes a classification of PSI or Particle Swarm Optimization (PSO) to Standard PSO. A SPSO is supposed to work on most optimization problems (difficult or easy). However, with different problem constraints, no universal SPSO can work for all problems efficiently. Based on the idea of mini-benchmarking proposed by Maurice Clere, specified PSO (SPPSO) algorithms are proposed in this paper to address the four different problems raised in Maurice Clere's work.