Automobile chain maintenance parts delivery problem using an improved ant colony algorithm

Gao, Junjie; Feng, Gu; Hu, Ping; Xie, Yanan; Yao, Baozhen

doi:10.1177/1687814016665297

Cited by 15 publications

(3 citation statements)

References 32 publications

(29 reference statements)

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“…In a publication on delivery problem of automotive parts, Gao et al (2016) presented a mutation operation and an adaptive ant‐tuple method for solving MDVRP with a time window. Likewise, Jabir et al (2017) developed an effective ACO and VNS research methodology to address MDGVRP for cost and emission reduction.…”

Section: Literature Reviewmentioning

confidence: 99%

Green vehicle routing problem: Metaheuristic solution with time window

Prakash

Pushkar

2022

Expert Systems

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The aim of a Green Vehicle Routing Problem is to find an optimal route for alternative fuel vehicles to minimize the overall travelling distances while reducing energy consumption and CO2emissions. In this problem each vehicle handles a subset of customers/orders, leaving from and returning to the depot, with respect to maximum distance travelled, while minimizing energy consumptions. We proposed a time window‐based GVRP solution (GVRP‐TW) with exact routing approach. Wherein, each route serves a subset of customers/orders with minimum intermediate refuelling/recharges. To test our method, we conducted experiments using MATLAB software on a set of three reference problem specimens (C‐101, R‐101 and RC‐11). Our approach, evaluated on these benchmark problems, par exceeds in performance in relation to the existing VRP methods (like tabu search, variable neighbourhood search, and GRASP). Moreover, the proposed GVRP‐TW can be further optimized to solve other VRP problems with energy minimisations and less intermediate stops.

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Section: Literature Reviewmentioning

confidence: 99%

Green vehicle routing problem: Metaheuristic solution with time window

Prakash

Pushkar

2022

Expert Systems

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“…Popular metaheuristic approaches are tabu search, genetic algorithms, simulated annealing, and ant colony optimization. Examples of such methods applied to MDVRP include works by Maischberger and Cordeau, 20 Vidal et al, 21 Yalian, 22 Gao, 23 and Ma et al 24…”

Section: Literature Reviewmentioning

confidence: 99%

Improvement in the model of cooperative aerial reconnaissance used in the tactical decision support system

Stodola

2017

Journal of Defense Modeling & Simulation

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This paper deals with the model of cooperative aerial reconnaissance. The goal of this high-level model is to explore the area of interest by a fleet of unmanned aerial systems optimally, which is (mostly) as fast as possible. The model has been implemented into the tactical decision support system to support commanders of the army of the Czech Republic in their decision making. The current paper does not present the model itself, but it enhances the original model by inserting a new parameter which is called angle delay coefficient. In the first part of the paper, the impact of the new parameter on the task of aerial reconnaissance is discussed. A series of experiments were proposed and conducted to verify the influence of the coefficient. The second part of the paper further improves the model by smoothing the routes of individual aerial systems; a new set of parameters are introduced.

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“…The amount of the pheromone deposited on the ground completely relies on the quality and quantity of the source discovered. [25][26][27][28] The quantity of the pheromone (tt) is intensified around the best objective value obtained throughout the simulation run in the continuous ACO algorithm. The location of the kth ant in the solution space is presented in the following equation…”

Section: Acomentioning

confidence: 99%

A hybrid optimization approach to forecast automobile sales of China

Gao

Xie

Feng

et al. 2017

Advances in Mechanical Engineering

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In this article, a novel Hybrid method based on particle swarm optimization and ant colony optimization (HPA) is proposed to forecast automobile sales of China. Proposed hybrid model integrating particle swarm optimization and ant colony optimization for estimation of Chinese automobile sales (HPAE) is the first model using aforementioned metaheuristic techniques. HPA is developed for automobile sales forecasting using highway mileage, gross domestic product, automobile ownership, and consumer price index. HPAE is developed in two forms including both Linear (HPAEL) and Quadratic (HPAEQ). Then, in order to show the accuracy of the algorithm, a comparison is made with ant colony optimization and particle swarm optimization. The results show that mean absolute errors of the HPAE model are the best among them, and better-fit solutions are provided by quadratic form (HPAEQ) due to fluctuations of the influential indicators in China.

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Automobile chain maintenance parts delivery problem using an improved ant colony algorithm

Cited by 15 publications

References 32 publications

Green vehicle routing problem: Metaheuristic solution with time window

Green vehicle routing problem: Metaheuristic solution with time window

Improvement in the model of cooperative aerial reconnaissance used in the tactical decision support system

A hybrid optimization approach to forecast automobile sales of China

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