Intelligent Bus Operation Optimization by Integrating Cases and Data Driven Based on Business Chain and Enhanced Quantum Genetic Algorithm

Lin, Haifeng; Tang, Chengpei

doi:10.1109/tits.2021.3121289

Cited by 18 publications

(9 citation statements)

References 35 publications

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“…On the other hand, [26] used large neighborhood search heuristic. In addition to VNS, tabu search [55,31], enhanced quantum genetic algorithm [22] and simulated annealing (SA) [8] are the other metaheuristics used in this context.…”

Section: 31mentioning

confidence: 99%

“…Thanks to the increasing importance of green issues and sustainability, minimizing energy consumption [17] started to find place in the objective functions. Minimizing the sum of total order processing time [25], minimizing the expected route duration plus penalties for late arrivals [2], minimizing the space [10], minimizing the waiting time cost of passengers [22], and minimizing the delays [51] are the other minimization based objective functions in the literature.…”

Section: 31mentioning

confidence: 99%

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A bibliometric and social network analysis of data-driven heuristic methods for logistics problems

Deniz

Özceylan

2023

JIMO

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<p style='text-indent:20px;'>Transport and logistics systems include a range of activities that deal with all sorts of decisions and operations from material handling to vehicle routing. One of the main challenges for transport and logistics processes is to deal with large-scale and complex problems. However, with increasingly diverse sets of operational real-world data becoming available, data-driven heuristic approaches are promising to pave the path for solving the problems in the field of transport and logistics. Thus, a comprehensive review is needed to observe the reflections of this path in literature. To bridge this gap, a total of 40 papers on the topic of "data-driven heuristic approaches to logistics and transportation problems" are determined. Before the categorization and content analysis; descriptive, bibliometric and social network analysis are carried out to identify the current state of the literature. All the papers are systemically reviewed based on different perspectives, namely data-driven methodology, heuristics, sub-problems and etc. Based on the review, suggestions for future research are likewise provided. Subsequently, machine learning and deep learning methods are considered to be among the most promising data-driven methodologies. The review may be useful for academicians, researchers, and practitioners for a better understanding of data-driven heuristic approaches to transportation and logistics problems.</p>

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Section: 31mentioning

confidence: 99%

Section: 31mentioning

confidence: 99%

A bibliometric and social network analysis of data-driven heuristic methods for logistics problems

Deniz

Özceylan

2023

JIMO

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“…The combination of quantum computation and genetic algorithm produces the quantum genetic algorithm, which is a probability-based evolutionary algorithm. Quantum genetic algorithm [34] is used to adaptively select the parameters of support vector machine (SVM) to improve the identification accuracy of the health state model of main pump.…”

Section: Qga Principlementioning

confidence: 99%

Health State Identification Method of Nuclear Power Main Circulating Pump Based on EEMD and OQGA-SVM

Liu

Zhu

et al. 2023

Electronics

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Main circulation pump is the only high-speed rotating equipment in primary loop of nuclear power plant. Its function is to ensure the normal operation of primary loop system by controlling the circulating flow of reactor coolant. In order to ensure long-term healthy operation of nuclear power main circulating pump, a method for identifying the health states of nuclear power main circulating pump based on ensemble empirical mode decomposition (EEMD) and support vector machine optimized by optimized quantum genetic algorithm (OQGA-SVM) is proposed. Vibration signal of main circulating pump is decomposed by EEMD. Vibration signal characteristics of nuclear power main circulating pump in healthy state and different fault states are analyzed and target characteristic indexes are put forward. Then, health state identification model of main circulation pump of OQGA-SVM is established, and target characteristic indexes are used as input parameter of the model. Finally, combined with experimental data, the model analysis and validation show that the health state identification method of nuclear power main circulating pump based on EEMD-OQGA-SVM can accurately and effectively identify the states of main circulation pump, has a higher identification accuracy than EEMD-SVM method and is more efficient and accurate than EEMD-QGA-SVM method.

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“…In recent years, inspired by bionic algorithms [10][11][12][13], researchers have tried to apply the improved ant colony algorithm (ACO) [14] to escape path generation in fire scenarios. In 2017 Hajjem M et al, applied the parallel ACO algorithm to indoor path planning to achieve dynamic real-time guidance [15].…”

Section: Introductionmentioning

confidence: 99%

The Escape Path PlanningAlgorithm in Large Building Fires Based on Multiple Fusion Strategies

Gao

Zhang

Wang

et al. 2023

Preprint

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Background: Large building fires are currently the most direct and serious type of fire that causes property damage and casualties, and delayed evacuation is one of the important reasons for casualties. Therefore, how to safely and quickly evacuate trapped individuals has become the focus of research by many scholars. Our goal is to propose a robust, universal, and high-precision fire escape path that utilizes minimal human intervention, making the algorithm practical and highly fitting to the scene. Results: This article constructs a framework for evacuating and evacuating fire personnel. Through the drone relay communication platform, multi-source information data collected at the fire scene is synchronously transmitted to the information exchange center, and uploaded to the cloud for real-time processing. In the cloud processing stage, the dynamic path planning method for large-scale building fires that integrates multiple strategies proposed in this article is used to generate escape paths, and the information exchange center is used to guide personnel to evacuate and escape. In addition, the information exchange center synchronizes the comprehensive scheduling of rescue agencies such as fire alarms and emergency centers. Conclusions: This article proposes a dynamic pathfinder path planning method that integrates multiple strategies based on the original FPA. By utilizing the mapping relationship between personnel location and fitness, the path planning problem is transformed into a set sorting problem, shortening escape time and improving path safety; A multi-objective path planning mechanism based on the A * algorithm has been constructed. By defining a dynamic matching degree to adapt to environmental changes, the population density at the exit is reduced, and the algorithm's global search ability and escape efficiency are improved. A cloud server IoT fire evacuation and escape model based on relay communication drones is designed, which utilizes the drone's adaptive height characteristics to ensure communication quality while expanding communication coverage, By using cloud processing to shorten runtime, the superiority of the method was verified through comparative experiments on single objective and multi-objective global path planning under multiple sets of grid maps with different specifications.

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Intelligent Bus Operation Optimization by Integrating Cases and Data Driven Based on Business Chain and Enhanced Quantum Genetic Algorithm

Cited by 18 publications

References 35 publications

A bibliometric and social network analysis of data-driven heuristic methods for logistics problems

A bibliometric and social network analysis of data-driven heuristic methods for logistics problems

Health State Identification Method of Nuclear Power Main Circulating Pump Based on EEMD and OQGA-SVM

The Escape Path PlanningAlgorithm in Large Building Fires Based on Multiple Fusion Strategies

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