Improved Hypercube Optimisation Search Algorithm for Optimisation of High Dimensional Functions

This paper proposes a stochastic search algorithm called improved hypercube optimisation (HOS+) to find better solution for problems. is an improvement of the that includes initialization, displacement-shrink and searching area modules. The proposed has new random parameters (RP) module uses two control in order prevent premature convergence slow finishing improve accuracy considerable. Many problems can sometimes cause getting stuck into interior local optimal solution. HOS+ solve this problem global A set experiments were done test performance algorithm. At first, tested using low high dimensional benchmark functions. simulation results indicated good much at lowest iterations. compared with other meta heuristic algorithms same functions on different dimensions. comparative superiority terms obtaining best value accelerating solutions.