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Cited by 28 publications
(14 citation statements)
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“…The solution portfolios obtained with the PSO solver outperformed those constructed using GA for all test problems in terms of Sharpe ratio and the established efficient frontier was above that of GA portfolios in all but one instance. Enhanced PSO algorithms for solving the multi-objective POP have been proposed by Deng et al [6] and He and Huang [12]. Cardinality and bounding constraints are incorporated by Deng et al [6], who find that their algorithm mostly outperforms GA, SA, and TS algorithms as well as previous PSO approaches especially in the case of low-risk portfolios.…”
Section: The Multi-objective Portfolio Optimization Problemmentioning
confidence: 99%
“…The solution portfolios obtained with the PSO solver outperformed those constructed using GA for all test problems in terms of Sharpe ratio and the established efficient frontier was above that of GA portfolios in all but one instance. Enhanced PSO algorithms for solving the multi-objective POP have been proposed by Deng et al [6] and He and Huang [12]. Cardinality and bounding constraints are incorporated by Deng et al [6], who find that their algorithm mostly outperforms GA, SA, and TS algorithms as well as previous PSO approaches especially in the case of low-risk portfolios.…”
Section: The Multi-objective Portfolio Optimization Problemmentioning
confidence: 99%
“…TSP is a NP-complete problem and it needs to be solved by some intelligent algorithms [19][20][21]. This paper utilized the discrete particle swarm algorithm [22] to search the optimal routes. Figure 6 illustrates the optimal fixed-routes for redistributing services in Tianyin Road metro station.…”
Section: Optimal Routes For Regular Redistributionmentioning
confidence: 99%
“…Compared with other optimization algorithms, PSO has many advantages such as simple concept, high performance and fast convergence, and has attracted researchers' attention to solve various benchmark functions or real-world (Hsiao et al 2014;Pluhacek et al 2014) engineering problems (Coelho 2010;Jiang et al 2013;He and Huang 2012;Zhan et al 2013). However, the performance of PSO suffers from control parameters such as inertial weight and acceleration coefficients.…”
Section: Introductionmentioning
confidence: 98%