A chessboard model for incompatible multi-component mass exchange network optimization
The incompatible multi-component mass exchange network is one of the difficult problems in mass exchange network synthesis.When simulating incompatible multi-component mass exchange networks,the traditional stage-wise superstructure model requires iterative calculation,resulting in complex optimization processes and compromised computational efficiency.To solve these problem,the chessboard model is applied to the incompatible multi-component mass exchange network,and the random walking algorithm with compulsive evolution(RWCE)based on population identification strategy is employed.The chessboard model simplifies the computational complexity of the simulation,and the population identification strategy solves the"agglomeration"phenomenon of individuals in the population.This approach comprehensively improves the computational efficiency of searching for the global optimal solution.A published example for the coke oven gas sweetening problem shows that the chessboard model and the RWCE based on population identification strategy can efficiently handle incompatible multi-component mass exchange networks,achieving faster average optimization time and minimizing the total annual cost.
process systemsmodelmass exchange networkalgorithmpopulation identification strategy
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