A Hybrid Intelligent Optimization Algorithm for an Unconstrained Single Level Lot-sizing Problem

Abstract

Scatter search algorithm (SSA) and shuffled frog leaping algorithm (SFLA) are two intelligent optimization algorithms. SSA was introduced to solve discrete optimization problems in 1977 and SFLA in 2003 was created for solving continuous optimization problems. Currently, These two algorithms had already been wildly applied to solving many engineering optimization problems. Within this paper, a hybrid algorithm, which combines SSA and SFLA, is presented in the hope that the hybrid algorithm can contribute a great deal to the advancement of intelligence optimization research. A test is done on an unconstrained single-level lot-sizing (SLLS) problem to further demonstrate the effectiveness and efficiency of this hybrid algorithm.