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Inspired by the search method of harmony search algorithms, we propose an other version of improved harmony search(IHS)algorithm to solve integer programming problems. This paper designs a novel improvising strategy which is beneficial to the convergence of algorithm in the early stage of iteration and increasing the diversity of population in the late stage of iteration. Experimental results show that the proposed algorithm can be an efficient alternative for solving integer programming problems.

An effective global harmony search algorithm (EGHS) is proposed to solve integer programming problems. The EGHS designs a novel location updating equation, which enables the improvised solution to move to the global best solution rapidly in each iteration. Random selection with a low probability is carried out for the improvised solution after updating location, for it can prevent the EGHS from being trapped into the local optimum. The results show that the EGHS can be an efficient alternative for solving integer programming problems.

Chemical equation balancing is an important issue in the field of chemistry, and it has drawn many researchers' attention over the last few decades. Essentially, chemical equation balancing can be classified as integer programming problem with equality constraints. In this paper, we use a recently proposed algorithm - the novel global harmony search algorithm (NGHS) to solve this problem. The NGHS algorithm is an improved version of harmony search algorithm (HS), and it includes two important operations: position updating and genetic mutation with a low probability. The former can enhance the convergence of the NGHS, and the latter can effectively prevent the NGHS from trapping into the local optimum. Based on a large number of experiments, the NGHS has demonstrated high efficiency on solving chemical equation balancing. The results show that the NGHS can be an efficient alternative for solving chemical equation balancing.