A Survey on Financial Applications of Metaheuristics

Soler‐Domínguez, Amparo; Juan, Ángel A.; Kizys, Renatas

doi:10.1145/3054133

“…Conventional optimization techniques are not effective in solving the ED problem; therefore, researchers have developed new optimization techniques known as ''metaheuristics'', which provide better solutions and overcome the demerits of conventional methods [25]. Moreover, they are applied to solve problems in many areas of engineering [26], [27], as well as other real-world optimization problems [28]- [30].…”

Section: Introductionmentioning

confidence: 99%

A Cauchy-Gaussian Quantum-Behaved Bat Algorithm Applied to Solve the Economic Load Dispatch Problem

Rugema¹,

Yan²,

Mugemanyi³

et al. 2021

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In this paper, a novel Cauchy-Gaussian quantum-behaved bat algorithm (CGQBA) is applied to solve the economic load dispatch (ELD) problem. The bat algorithm (BA) is an acknowledged metaheuristic optimization algorithm owing to its performance. However, the classical BA presents some weaknesses, such as premature convergence. To withstand the drawbacks of the BA, quantum mechanics theories and Gaussian and Cauchy operators are integrated into the standard BA to enhance its effectiveness. Since the economic load dispatch is a nonlinear, complex and constrained optimization problem, its main objective is to reduce the total generation cost while matching the equality and inequality constraints of the system. The validity of the CGQBA is tested on six standard benchmark functions with different characteristics. The numerical results indicate that the CGQBA is effective and superior to many other algorithms. Moreover, the CGQBA is applied to solve the ELD problems on various test systems including 3,6,20, 40,110 and 160 implemented generating units. The simulation results illustrate the strength of the CGQBA compared with other algorithms recently reported in the literature.

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“…Metaheuristic-based techniques inspired by the behaviour of natural phenomena [1], swarm intelligence [2], or physical processes [3] have been extensively used in wide range of applications in science and engineering [4][5][6][7][8]. The era of metaheuristic techniques started by Genetic Algorithm (GA) which was introduced by Holland in 1960 [9] inspired by the theory of evolution in biology.…”

Section: Introductionmentioning

confidence: 99%

An enhanced Moth-flame optimization algorithm for permutation-based problems

Helmi

¹

,

Alenany

²

2020

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Moth-flame optimizer (MFO) is one of the recently proposed metaheuristic optimization techniques which has been successfully used in wide range of applications. However, there are two issues with the MFO algorithm. First, as a stochastic technique, MFO may prematurely converge at some local minima during the search process. Second, the original MFO was developed for continuous search space problems and is not directly applicable to, e.g., permutation-based problems (PBP). In this paper, a novel perturbation strategy is introduced to the MFO algorithm to avoid probable local minima regions. This strategy works as follows: if the best solution obtained so far doesn't improve for a given number of consecutive iterations, the current population of solutions is perturbed using some crossover mechanism as an attempt to explore new promising neighbourhoods in the search space. In addition, smallest position values mapping technique is employed in order for the proposed, termed CrossMFO (COMFO), algorithm to be applicable to PBP problems. It is noticed that, despite these modifications, the proposed COMFO has the same time complexity order as the original MFO. Extensive simulation experiments are conducted to compare the proposed COMFO to the MFO, other enhanced versions of MFO, and some metaheuristic optimizers in solving the well-known Travelling Salesman Problem (TSP). Empirical results show that the solutions obtained using MFO are improved by a factor of 24-47% on average for large TSP instances having more than 100 cities using COMFO and can even reach 38-58% using different settings. In addition, compared to other algorithms in the literature, the proposed algorithm provides, on average, better solutions. Hence, it can be considered a promising and efficient technique for this type of problems.

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“…Conventional optimization techniques are not effective in solving the ED problem; therefore, researchers have developed new optimization techniques known as "metaheuristics", which provide better solutions and overcome the demerits of conventional methods [25]. Moreover, they are applied to solve problems in many areas of engineering [26]- [27], as well as other real-world optimization problems [28]- [30].…”

Section: Introductionmentioning

confidence: 99%

A Cauchy-Gaussian Quantum-Behaved Bat Algorithm Applied to Solve the Economic Load Dispatch Problem

Rugema

¹

,

Yan

²

,

Mugemanyi

³

et al. 2020

View full text Add to dashboard Cite

In this paper, a novel Cauchy-Gaussian quantum-behaved bat algorithm (CGQBA) is applied to solve the economic load dispatch (ELD) problem. The bat algorithm (BA) is an acknowledged metaheuristic optimization algorithm owing to its performance. However, the classical BA presents some weaknesses, such as premature convergence. To withstand the drawbacks of the BA, quantum mechanics theories and Gaussian and Cauchy operators are integrated into the standard BA to enhance its effectiveness. Since the economic load dispatch is a nonlinear, complex and constrained optimization problem, its main objective is to reduce the total generation cost while matching the equality and inequality constraints of the system. The validity of the CGQBA is tested on six standard benchmark functions with different characteristics. The numerical results indicate that the CGQBA is effective and superior to many other algorithms. Moreover, the CGQBA is applied to solve the ELD problems on various test systems including 3,6,20, 40,110 and 160 implemented generating units. The simulation results illustrate the strength of the CGQBA compared with other algorithms recently reported in the literature.

show abstract

A Survey on Financial Applications of Metaheuristics

Cited by 50 publications

References 117 publications

A Cauchy-Gaussian Quantum-Behaved Bat Algorithm Applied to Solve the Economic Load Dispatch Problem

A Cauchy-Gaussian Quantum-Behaved Bat Algorithm Applied to Solve the Economic Load Dispatch Problem

An enhanced Moth-flame optimization algorithm for permutation-based problems

A Cauchy-Gaussian Quantum-Behaved Bat Algorithm Applied to Solve the Economic Load Dispatch Problem

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