A hybrid Genetic Algorithm for Vehicle Routing Problem with Time Windows

J, Sripriya; Ramalingam, A.; Rajeswari, K. Raja

doi:10.1109/iciiecs.2015.7193072

Cited by 8 publications

(6 citation statements)

References 10 publications

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“…First proposed by Professor J.Holland [9] in 1975, the genetic algorithm was used to solve the VRP with great randomness when performing crossover and variation, and the algorithm had disadvantages such as easy premature maturity and slow convergence, so many scholars have made relevant improvements to the genetic algorithm. [10][11] [12][13][14]…”

Section: Model Solving Algorithm Designmentioning

confidence: 99%

Study on Scheduling of Metro Construction Muck Transport Vehicles during Restricted Hours Based on Improved Genetic Algorithm

2022

AJETS

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For the time scheduling problem of each station's muck transportation vehicle and muck processing center during the construction of the under-construction subway station, a muck transportation time scheduling optimization model with the shortest vehicle waiting time and processing plant waiting time as the objective function is established, and the genetic algorithm is improved by repairing the chromosomes of the individuals who violate the constraints and introducing the elite strategy. The effectiveness of the model and algorithm is verified by examples. The results show that the proposed model can efficiently perform unified scheduling for the transportation of spoil at multiple construction sites, and the designed algorithm has good merit-seeking capability.

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Section: Model Solving Algorithm Designmentioning

confidence: 99%

Study on Scheduling of Metro Construction Muck Transport Vehicles during Restricted Hours Based on Improved Genetic Algorithm

2022

AJETS

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“…[31,32] The specific concept is: assuming the problems to be solved are the process of biological evolution; eliminate the solutions that do not adapt to the task through a series of processes, such as crossover, mutation and evolution; retain the highly adaptable solutions in the later generation and repeatedly evolve; and finally obtain the optimal solution by decoding the optimal individuals in the last generation. [33] Therefore, in this paper, obtaining the optimal network structure can be considered as a task requiring constant evolution, and the optimal n 1 and n 2 values can be regarded as the optimal solution to the problem. The overall operation process is shown in Fig.…”

Section: Automatic Parameter Searching By Using the Genetic Algorithmmentioning

confidence: 99%

“…To speed up the efficiency of mutation, a polynomial mutation operator is used in this paper. [33,37] The order of decision variables was determined according to fitness, and the individuals corresponding to decision variables were mutated according to the polynomial mutation mechanism.…”

Section: Automatic Parameter Searching By Using the Genetic Algorithmmentioning

confidence: 99%

A spintronic memristive circuit on the optimized RBF-MLP neural network

Gao¹,

Li²,

Jiang³

et al. 2022

Chinese Phys. B

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Radial basis function network (RBF) has excellent generalization ability and approximation accuracy when parameters set properly.However, relying only on traditional methods,it is tough to obtain optimal network's parameters and construct a stabile model as well.In view of this,RBF-MLP neural network is proposed in this article.In the form of connecting two networks to work cooperatively,the RBF's parameter can be adjusted adaptively by the structure of multi-layer perceptron (MLP) so as to realize the effect of backpropagation updating error. Furthermore, genetic algorithm is used to optimize the network's hidden layer so as to confirm the optimal neurons (basis function) number automatically. In addition, a memristive circuit model is proposed to realize the neural network's operation mentioned above based on the character of spin memristors. It is verified that the network can adaptively construct a network model with outstanding robustness and stably achieve 98.33% accuracy in processing the MNIST dataset classification task. The experimental results show that the method mention above has application value.

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“…Taner et al [17] developed two metaheuristic algorithms to solve the VRPTW, the SA algorithm and an iterated local search (ILS). Sripriya et al [18] designed a hybrid genetic search with diversity control using a GA to solve the VRPTW, using the Pareto approach and two mutation operators to find the optimal solution set.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The characteristics of the dealerships (time windows), the NCSY and the auto-carriers (capacity), as well as different operational restrictions on the routes, bring forth the VRPTW, several authors [14][15][16][17][18] have worked on this variant of the VRP. In this case, study the term vehicle denotes a transported item (e.g., a car, a van), the term auto-carrier denotes a truck transporting vehicles, and the term dealership denotes a delivery point (i.e., a customer requiring one or more vehicles).…”

Section: Problem Definition and Mathematical Modelmentioning

confidence: 99%

A Heuristic Algorithm for the Routing and Scheduling Problem with Time Windows: A Case Study of the Automotive Industry in Mexico

et al. 2019

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This paper investigates a real-world distribution problem arising in the vehicle production industry, particularly in a logistics company, in which cars and vans must be loaded on auto-carriers and then delivered to dealerships. A solution to the problem involves the loading and optimal routing, without violating the capacity and time window constraints for each auto-carrier. A two-phase heuristic algorithm was implemented to solve the problem. In the first phase the heuristic builds a route with an optimal insertion procedure, and in the second phase the determination of a feasible loading. The experimental results show that the purposed algorithm can be used to tackle the transportation problem in terms of minimizing total traveling distance, loading/unloading operations and transportation costs, facilitating a decision-making process for the logistics company.

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A hybrid Genetic Algorithm for Vehicle Routing Problem with Time Windows

Cited by 8 publications

References 10 publications

Study on Scheduling of Metro Construction Muck Transport Vehicles during Restricted Hours Based on Improved Genetic Algorithm

Study on Scheduling of Metro Construction Muck Transport Vehicles during Restricted Hours Based on Improved Genetic Algorithm

A spintronic memristive circuit on the optimized RBF-MLP neural network

A Heuristic Algorithm for the Routing and Scheduling Problem with Time Windows: A Case Study of the Automotive Industry in Mexico

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