In addition, swarm intelligence based search algorithms for multiobjective optimization [13-15] have also been developed and applied to a variety of MOOPs. Several more recently developed multiobjective algorithms [16-19] based on the search techniques other than the ones used in genetic algorithm  or EAs and particle swarm optimization  have also shown a great potential in obtaining the Pareto front closest to the true Pareto front.
In the present paper a multiobjective heat transfer search (MOHTS) algorithm for solving MOOPs is proposed and has been applied to the MOOP of optimizing the suspension parameters of the half car model with driver's seat having total five degrees of freedom as used in [21-23] to evaluate the potential of the proposed MOHTS algorithm.
In this study a nonlinear MOOP of optimizing the vehicle suspension system design having conflicting objectives is optimized.
Firstly the half car MOOP with five conflicting objective functions as used in [21-23] is employed in numerical study 1 to test and compare the performance of MOHTS with NSGA-II, MUGA , and with the combined PSO and GA based MOEA ; secondly another half car MOOP with a different set of five more realistic conflicting objective functions from the ones used in numerical study 1 is formulated and tested on the platforms of MOHTS and NSGA-II.
(1.) Wilson, R., "Know your M0PPS from your MOOPS in medical power supply design," ElectronicsWeekly.com, Nov.
Such a supply can help you comply with relevant EMC and medical safety standards and achieve the proper levels of Method of Patient Protection (MOPP) and Method of Operator Protection (MOOP): 1 x MOPP and 1 x MOOP or the more stringent 2 x MOPP and 2 x MOOP.
PO solutions are the set of solutions given by MOOP which are nondominating in nature.
As these objectives are conflicting in nature, solving the MOOP helps in obtaining the PO or tradeoff solutions among various conflicting objectives.
MOOP has been performed by integrating the validated model with a well-established multi objective optimization routine, real-coded non-dominated sorting genetic algorithm (NSGA II) .
Since EAs deal with a group of candidate solutions, it seems natural to use them in MOOPs to find a group of optimal solutions.
It was thus concluded that DEMO may be adopted as an alternative for solving MOOPs.
Therefore, this study further corroborates that CPMDE is adoptable as a method of EMOA for solving real-world MOOPs.