Data mining-based firefly algorithm for green vehicle routing problem with heterogeneous fleet and refueling constraint

Behnamian, J.; Ghadimi, M.; Farajiamiri, Mina

doi:10.1007/s10462-022-10336-9

Cited by 7 publications

(3 citation statements)

References 63 publications

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“…Cheng et al 19 developed a mixed integer programming model to minimize the total carbon footprint and penalty cost of delayed orders in efficient fishbone warehouse layouts with dynamic arrival orders and transportation time constraints in joint order batch processing and picking routing problems. Behnamian et al 20 proposed a mathematical model for the green heterogeneous vehicle routing problem and developed the firefly algorithm in large-scale examples to solve the problem. Chen et al 21 studied the cold chain green multi warehouse vehicle routing problem (CC-GMD-VRPTW-MF) with time windows and mixed fleets for urban logistics distribution using electric vehicles (EVs) and gasoline diesel vehicles (GDVs).…”

Section: Literature Reviewmentioning

confidence: 99%

Multi-objective green vehicle scheduling problem considering time window and emission factors in ship block transportation

Guo,

Wang,

Sun

et al. 2024

Sci Rep

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Logistics distribution is one of the main sources of carbon dioxide emissions at present, and there are also such distribution problems in the shipbuilding process. With the increasing attention paid to environmental problems, how to effectively reduce the energy consumption of block transportation and improve the utilization rate of resources in the factory is the key problem that China’s shipbuilding industry needs to solve at present. This article considers the time windows for block transportation tasks, as well as the self-loading constraints of different types of flat cars, and establishes an optimization model that minimizes the empty transport time and energy consumption of the flat cars as the optimization objective. Then, an Improved Genetic Whale Optimization Algorithm is designed, which combines the cross and mutation ideas of genetic algorithms and proposes a whale individual position updating mechanism under a mixed strategy. Furthermore, the performance and computational efficiency of the algorithm are verified through comparative analysis with other classical optimization algorithms on standard test examples. Finally, the shipyard’s block transportation example proves that the energy-saving ship block transportation scheduling method can effectively improve the efficiency of shipbuilding enterprise’s block transportation and reduce the energy consumption in the block transportation process. It proves the engineering practicality of the green dispatching method proposed in this paper, which can further provide a decision-making method for shipyard managers.

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Section: Literature Reviewmentioning

confidence: 99%

Multi-objective green vehicle scheduling problem considering time window and emission factors in ship block transportation

Guo,

Wang,

Sun

et al. 2024

Sci Rep

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show abstract

“…The authors used arc-duplicating and name-duplicating formulations to solve the problem, and their study reveals that, in most cases, arc-duplicating formulation prefers better. Behnamian et al (2023) take into account situations where the vehicle is running low on clean fuel and thus needs to be refueled. They present a mathematical formulation for a green heterogeneous vehicle routing problem and develop a firefly algorithm to solve the problem in large-size instances.…”

Section: Literature Reviewmentioning

confidence: 99%

A green vehicle routing problem with picking up and delivery based on an improved firefly algorithm

Zhou

2023

Preprint

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Transportation which plays an essential role in distribution impacts climate change and global warming. So, one of the critical problems in distribution is the green vehicle routing problem. This paper investigates a green vehicle routing problem with picking up and delivery and soft time windows for a single depot. The problem is developed as a single-objective mixed integer nonlinear programming model. The model aims to minimize fuel costs based on vehicle load and penalty costs for violating time windows while satisfying customer pickup and delivery demands simultaneously. This paper proposes an improved firefly algorithm based on chaotic initialization and differential evolution to solve the model. Results show that the proposed model minimizes carbon emissions while maximizing customer satisfaction. Compared with a traditional heuristic algorithm, the improved firefly algorithm has higher solved precision.

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“…Generally, sensors are used to collect data from machines and processes. The data integration combines the data that comes from different resources (14) . The data cleaning handles the noisy data, filling in missing values by using some pattern, making consistency in data, removing the outliers from the data set, and making it an improved version of data.…”

Section: Literature Reviewmentioning

confidence: 99%

Data Mining and Predictive Analytics for Injection Molding: An Analysis

Kumari,

Saini

2023

IJST

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Objectives:The objective of the research is to focus on the quality product of injection molding for the automobile industry. The root cause of the defects in the product needs to be understood in order to improve the product quality. Method: The research represents an industry Standard Process for Data Mining (CRISP-DM) framework for molding quality improvement. The Logistic Regression, AI ML algorithm has been used to develop the model. Because Logistic Regression is a classification supervised algorithm and our dependent variable also belongs to classification so used this algorithm. Splits the data set for training (66.66%) and testing (33.33%) of the model. Findings: During the literature review, it was found that some of the researchers focused on minimizing the variation in the product quality by considering the filling and packing stage, but only these parameters' impact on product quality is not sufficient. Considering the limitation as done by many researchers, the presented research work on molding parameters. The presented research considers multiple process-independent variables and their range as mould weight, the temperature of mold and material, injection time, hold time, plastification time, cooling time, and total cycle time and one dependent variable like quality. Novelty: The novelty of this research is that it is detailing and focus on the quantity of molded items and all independent parameters that impact the dependent parameter (quality) of molded items during the injection molding process. Therefore, this model performs the prediction of the molded items' quality based on their parameter values and sends an alarm or notification to the respective teams. The analysis has been done based on a pattern they find from a machine or database, and it returns the outcome, which can be a prediction.

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Data mining-based firefly algorithm for green vehicle routing problem with heterogeneous fleet and refueling constraint

Cited by 7 publications

References 63 publications

Multi-objective green vehicle scheduling problem considering time window and emission factors in ship block transportation

Multi-objective green vehicle scheduling problem considering time window and emission factors in ship block transportation

A green vehicle routing problem with picking up and delivery based on an improved firefly algorithm

Data Mining and Predictive Analytics for Injection Molding: An Analysis

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