Sharing mutation genetic algorithm for solving multi-objective problems

Hsieh, Sheng-Ta; Chiu, Shih-Yuan; Yen, Shi-Jim

doi:10.1109/cec.2011.5949838

Cited by 2 publications

(1 citation statement)

References 13 publications

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“…The mine water reuse problem in this paper is summed up as a multi-objective optimization problem. Both particle swarm optimization (PSO) and genetic algorithm (GA) have great advantages and convenience for solving multi-objective optimization problems [ 43 , 44 , 45 , 46 ]. Therefore, this paper will make use of the respective advantages of particle swarm optimization and genetic algorithm to optimize the mine water distribution.…”

Section: Hybrid Improved Algorithm Based On Genetic Algorithms and Pa...mentioning

confidence: 99%

Economic Optimal Allocation of Mine Water Based on Two-Stage Adaptive Genetic Algorithm and Particle Swarm Optimization

Zhang

Yang

et al. 2022

Sensors

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The waste mine water is produced in the process of coal mining, which is the main cause of mine flood and environmental pollution. Therefore, economic treatment and efficient reuse of mine water is one of the main research directions in the mining area at present. It is an urgent problem to use an intelligent algorithm to realize optimal allocation and economic reuse of mine water. In order to solve this problem, this paper first designs a reuse mathematical model according to the mine water treatment system, which includes the mine water reuse rate, the reuse cost at different stages and the operational efficiency of the whole mine water treatment system. Then, a hybrid optimization algorithm, GAPSO, was proposed by combining genetic algorithm (GA) and particle swarm optimization (PSO), and adaptive improvement (TSA-GAPSO) was carried out for the two optimization stages. Finally, simulation analysis and actual data detection of the mine water reuse model are carried out by using four algorithms, respectively. The results show that the hybrid improved algorithm has better convergence speed and precision in solving the mine water scheduling problem. TSA-GAPSO algorithm has the best effect and is superior to the other three algorithms. The cost of mine water reuse is reduced by 9.09%, and the treatment efficiency of the whole system is improved by 5.81%, which proves the practicability and superiority of the algorithm.

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Section: Hybrid Improved Algorithm Based On Genetic Algorithms and Pa...mentioning

confidence: 99%