An Event-Based Supply Chain Partnership Integration Using a Hybrid Particle Swarm Optimization and Ant Colony Optimization Approach

Lü, Zhigang; Wang, Hui

doi:10.3390/app10010190

Cited by 6 publications

(3 citation statements)

References 46 publications

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“…Soleimani et al [ 37 ] proposed a hybrid particle swarm algorithm and genetic algorithm to solve the problem based on the advantages and disadvantages of particle swarm algorithm and genetic algorithm when studying the problem of designing a large-scale network closed-loop supply chain network. Lu et al [ 38 ] combined the global search capability of PSO with the powerful evolutionary capability of ACO and a bit of positive feedback to solve the multi-objective supply chain partner integration problem.…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-objective sustainable supply chain network optimization based on chaotic particle—Ant colony algorithm

et al. 2023

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For the optimal design of the sustainable supply chain network, considering the comprehensiveness of the problem factors, considering the three aspects of economy, environment and society, the goal is to minimize the establishment cost, minimize the emission of environ-mental pollution and maximize the number of labor. A mixed integer programming model is established to maximize the efficiency of the supply chain network. The innovation of this paper, first, is to consider the impact of economic, environmental and social benefits in a continuous supply chain, where the environmental benefits not only consider carbon emissions but also include the emissions of plant wastewater, waste and solid waste as influencing factors. Second, a multi-objective fuzzy affiliation function is constructed to measure the quality of the model solution in terms of the overall satisfaction value. Finally, the chaotic particle ant colony algorithm is proposed, and the problem of premature convergence in the operation of the particle swarm algorithm is solved. Experimental results show that the PSCACO algorithm proposed in this paper is compared with MOPSO, CACO and NSGA-II algorithms, and the convergence effect of the algorithm is concluded to be more effective to verify the effectiveness and feasibility of chaotic particle ant colony algorithm for solving multi-objective functions, which proposes a new feasible solution for the supply chain management.

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Section: Literature Reviewmentioning

confidence: 99%

Multi-objective sustainable supply chain network optimization based on chaotic particle—Ant colony algorithm

et al. 2023

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“…The PSO algorithm is a population-based meta-heuristic that was proposed by Kennedy and Eberhart [5]. It is based on simulating the foraging behavior of bird flocking, and it has been widely used in many fields, such as benchmark function optimization [6], image processing [7], scheduling decision [8], and engineering [9]. However, it is well-known that the classical PSO algorithm yields premature convergence.…”

Section: Introductionmentioning

confidence: 99%

An Investigation of Particle Swarm Optimization Topologies in Structural Damage Detection

Serra

Olivier

2021

Applied Sciences

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In the past few decades, vibration-based structural damage detection (SDD) has attracted widespread attention. Using the response data of engineering structures, the researchers have developed many methods for damage localization and quantification. Adopting meta-heuristic algorithms, in which particle swarm optimization (PSO) is the most widely used, is a popular approach. Various PSO variants have also been proposed for improving its performance in SDD, and they are generally based on the Global topology. However, in addition to the Global topology, other topologies are also developed in the related literature to enhance the performance of the PSO algorithm. The effects of PSO topologies depend significantly on the studied problems. Therefore, in this article, we conduct a performance investigation of eight PSO topologies in SDD. The success rate and mean iterations that are obtained from the numerical simulations are considered as the evaluation indexes. Furthermore, the average rank and Bonferroni-Dunn’s test are further utilized to perform the statistic analysis. From these analysis results, the Four Clusters are shown to be the more favorable PSO topologies in SDD.

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“…This problem can be solved by ant colony optimization algorithm [28]- [30]. Lu and Wang [31] proposes an eventbased model which lists the events related with all phases of cooperation with partners and puts events into a dynamic supply chain network in order to understand factors that affect supply chain partnership integration. They develop a multi-objective supply chain partnership integration problem by maximizing trustworthiness, supplier service, qualified products rate and minimizing cost, and then, apply a hybrid algorithm with particle swarm optimization and ant colony optimization that aims to efficiently solve the problem.…”

Section: Introductionmentioning

confidence: 99%

Tilting Path Optimization of Tilt Quad Rotor in Conversion Process Based on Ant Colony Optimization Algorithm

Wu¹,

Wang²,

Duan

et al. 2020

IEEE Access

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The tilt quad rotor (TQR) has the problem of manipulation redundancy due to the aerodynamic structure changing in conversion mode. The tilting path is limited by the conversion corridor. In order to solve the problem of manipulation redundancy in conversion mode and find out the optimal tilting path in conversion corridor, the aerodynamic model of the TQR based on Goldstein vortex theory is established to obtain the manipulation derivative matrix and conversion corridor. A novel manipulation strategy is proposed, the altitude, forward velocity and tilt angle are introduced into the manipulation strategy to ensure the stability of the altitude and attitude in conversion process. To find out the optimal tilting path in conversion corridor, a novel tilting strategy is proposed based on Ant Colony Optimization (ACO) algorithm and compared with another three tilting path. To verify the credibility of the flight dynamics model, the effectiveness of manipulation strategy and tilting path optimization, the simulation and flight test were carried out. The simulation and flight test results show that the manipulation strategy proposed in this paper can solve the manipulation redundancy in conversion mode very well, and the proposed tilting path can ensure the stability of the altitude and attitude in conversion corridor.INDEX TERMS Tilt quad rotor, manipulation strategy, ant colony optimization, tilting path, flight test.

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An Event-Based Supply Chain Partnership Integration Using a Hybrid Particle Swarm Optimization and Ant Colony Optimization Approach

Cited by 6 publications

References 46 publications

Multi-objective sustainable supply chain network optimization based on chaotic particle—Ant colony algorithm

Multi-objective sustainable supply chain network optimization based on chaotic particle—Ant colony algorithm

An Investigation of Particle Swarm Optimization Topologies in Structural Damage Detection

Tilting Path Optimization of Tilt Quad Rotor in Conversion Process Based on Ant Colony Optimization Algorithm

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