An Improved Equilibrium Optimizer Algorithm for Flexible Job Shop Scheduling Problem
Aimimg at low accuracy and poor stability of the original equilibrium optimizer algorithm in solving the job shop scheduling problem,a improved multipopulation quantum equilibrium optimizer(IMQEO)based on unidirectional multi-popula-tion information exchange is proposed.Firstly,the initial balance pool is divided into three sub-balance pools.One balance pool is mainly used for exploitation,and the other balance pools are mainly used for space exploration to find the optimal solution efficient-ly.Then,the components of the optimal concentration are separated,and multiple optimal concentrations are reconstructed.Com-bined with the greedy strategy,the individuals are successively surrounded and contracted to each optimal concentration to realize accelerated convergence.Finally,a quantum revolving door strategy is used to update the concentration to jump out of the local opti-mal solution.Compared with EO,the results show that the hybrid improvement strategy has a better optimization effect.
multi-populationequilibrium optimizerquantum rotation gateflexible job shop scheduling problem
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