Abstract
electromagnetism-like mechanism (em) algorithm, a meta-heuristic algorithm for global optimisation, utilises an attraction-repulsion mechanism to move the sample points towards the optimality. the original em has a strong ability for diversification. and a simple random line search algorithm for local search has been added to improve its intensification. however, it plays a quite limited role and the performance of the original em is not satisfactory. therefore, in this paper, a modified solis and wets local search is proposed to improve the performance of em. two self-adapt parameters are introduced into solis and wets local search. in addition, an accelerated force formula is adopted for high-dimensional function optimisation. some benchmark test problems have been used to evaluate the proposed-algorithm. results obtained are compared with those from other algorithms including original em algorithm and all kinds of particle swarm optimisation methods. the comparisons show that the novel em has achieved significant improvement.
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