Particle swarm optimization based-algorithms to solve the two-machine cross-docking flow shop problem: just in time scheduling

Hamdi, Imen; Boujneh, Imen

doi:10.1007/s10878-022-00871-0

Cited by 4 publications

(1 citation statement)

References 31 publications

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“…Second, the automobile engine is a complex, diverse and extremely important system, which works under various functions, including fuel supply, ignition timing and fuel saving. Fault diagnosis and analysis play an important role in the normal and smooth operation of the whole vehicle [13][14]. Third, through comprehensive and detailed inspection and maintenance of the automobile engine, we can find out the problem in time and take corresponding measures to reduce or avoid some unnecessary losses.…”

Section: Importance Of Automobile Engine Fault Diagnosismentioning

confidence: 99%

Fusion Particle Swarm Optimization Algorithm in Automobile Engine Fault Diagnosis

2023

KME

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The automobile engine is a high-speed vehicle. Its working principle and process are to generate gas through fuel burning, and then convert the chemical energy contained in the exhaust gas into heat energy. However, in reality, due to various reasons, serious wear and tear inside the engine and sharp reduction of mechanical strength have occurred. This paper mainly introduces a method based on particle swarm optimization algorithm to simplify the complex structure between various systems in the car and outside. The analysis shows that this method has the advantages of accuracy and reliability, and can effectively diagnose and predict it. The advantage of large workload and small space is very prominent. After that, this paper designs a fault diagnosis model of automobile engine based on particle swarm optimization algorithm, and tests the model. The test results show that the fault diagnosis time of this model is short, and the fault diagnosis accuracy is high, which can meet the user needs.

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Section: Importance Of Automobile Engine Fault Diagnosismentioning

confidence: 99%

Fusion Particle Swarm Optimization Algorithm in Automobile Engine Fault Diagnosis

2023

KME

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Modelling of Cross-Docking Terminal-Based Supply Chain Solutions in Industry 4.0 Era

Bányai

2024

Lecture Notes in Logistics

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A hybrid genetic algorithm based on reinforcement learning for the energy-aware production scheduling in the photovoltaic glass industry

Cui,

Yuan

2024

Computers & Operations Research

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Particle swarm optimization based-algorithms to solve the two-machine cross-docking flow shop problem: just in time scheduling

Cited by 4 publications

References 31 publications

Fusion Particle Swarm Optimization Algorithm in Automobile Engine Fault Diagnosis

Fusion Particle Swarm Optimization Algorithm in Automobile Engine Fault Diagnosis

Modelling of Cross-Docking Terminal-Based Supply Chain Solutions in Industry 4.0 Era

A hybrid genetic algorithm based on reinforcement learning for the energy-aware production scheduling in the photovoltaic glass industry

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