Discrete Firefly Algorithm for Clustered Multi-Temperature Joint Distribution with Fuzzy Travel Times

Lu, Sichao; Wang, Xifu

doi:10.2991/ijcis.11.1.15

Cited by 3 publications

(2 citation statements)

References 26 publications

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“…These problems are often difficult to solve due to their diverse properties, such as nonlinearity, nondifferentiability, multi-modality and nonseparability. During last decades many metaheuristic algorithms have been proposed for solving hard optimization problems [1][2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Firefly and Multi-Strategy Artificial Bee Colony Algorithm

Brajević¹,

Stanimirović²,

Li³

et al. 2020

IJCIS

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Many hard optimization problems have been efficiently solved by two notable swarm intelligence algorithms, artificial bee colony (ABC) and firefly algorithm (FA). In this paper, a collaborative hybrid algorithm based on firefly and multi-strategy artificial bee colony, abbreviated as FA-MABC, is proposed for solving single-objective optimization problems. In the proposed algorithm, FA investigates the search space globally to locate favorable regions of convergence. A novel multi-strategy ABC is employed to perform local search. The proposed algorithm incorporates a diversity measure to help in the switch criteria. The FA-MABC is tested on 40 benchmark functions with diverse complexities. Comparative results with the basic FA, ABC and other recent state-of-the-art metaheuristic algorithms demonstrate the competitive performance of the FA-MABC.

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Section: Introductionmentioning

confidence: 99%

A Hybrid Firefly and Multi-Strategy Artificial Bee Colony Algorithm

Brajević¹,

Stanimirović²,

Li³

et al. 2020

IJCIS

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show abstract

“…The FA is effective metaheuristic technique, which has simple concept and easy implementation. Therefore the FA has been studied by many researchers and new FA variants have been described to solve different classes of optimization problems, such as continuous, combinatorial, constrained, multi-objective, dynamic and noisy optimization 20,21,22,23,24 .…”

Section: Introductionmentioning

confidence: 99%

An improved chaotic firefly algorithm for global numerical optimization

Brajević¹,

Stanimirović²

2018

IJCIS

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Firefly algorithm (FA) is a prominent metaheuristc technique. It has been widely studied and hence there are a lot of modified FA variants proposed to solve hard optimization problems from various areas. In this paper an improved chaotic firefly algorithm (ICFA) is proposed for solving global optimization problems. The ICFA uses firefly algorithm with chaos (CFA) as the parent algorithm since it replaces the attractiveness coefficient by the outputs of the chaotic map. The enhancement of the proposed approach involves introducing a novel search strategy which is able to obtain a good ratio between exploration and exploitation abilities of the algorithm. The impact of the introduced search operator on the performance of the ICFA is evaluated. Experiments are conducted on nineteen well-known benchmark functions. Results reveal that the ICFA is able to significantly improve the performance of the standard FA, CFA and four other recently proposed FA variants.

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Design of A Freight Transport System for Highway Rest Areas

Wen

Liu

et al. 2021

IOP Conf. Ser.: Earth Environ. Sci.

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The rest area is an important place for travelers to have a rest. Therefore, it should be replenished with a variety of goods in time. This article introduces a freight transport system for highway rest areas, including conceptual framework, a mathematical model and its algorithm. The model has two objective functions which aim to minimize transport time as well as maximizing the priority value of highway rest areas. To solve this multi-objective optimization problem, a discrete firefly algorithm which was proposed to solve the multi-temperature joint distribution is extended. To validate the performance of the algorithm, simulation experiments are carried out and the experimental results show that the discrete firefly algorithm is effective for the problem.

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Discrete Firefly Algorithm for Clustered Multi-Temperature Joint Distribution with Fuzzy Travel Times

Cited by 3 publications

References 26 publications

A Hybrid Firefly and Multi-Strategy Artificial Bee Colony Algorithm

A Hybrid Firefly and Multi-Strategy Artificial Bee Colony Algorithm

An improved chaotic firefly algorithm for global numerical optimization

Design of A Freight Transport System for Highway Rest Areas

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