An adaptive large neighborhood search for the larger-scale multi depot green vehicle routing problem with time windows

Wen, Muyang; Sun, Wei; Yu, Yang; Tang, Jiafu; Kaku, Ikou

doi:10.1016/j.jclepro.2022.133916

Cited by 25 publications

(8 citation statements)

References 49 publications

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“…The total carbon emission cost is derived from the carbon generated by the vehicle used er and the carbon tax cost Pe. In the calculation of carbon emissions produced by the vehicle, we adopt the formulation developed by Wen et al [63]. The formulation for carbon emission cost calculation is influenced by carbon emission parameter er, the distance between the starting and ending points di, the average vehicle speed v, individual vehicle capacity Ck, the weight of the payload transported from the starting to the ending point wij k , and parameter α 1 and α 2 .…”

Section: Problem Formulationmentioning

confidence: 99%

Multi-Vehicle Capacitated Vehicle Routing Problem for Rice Commodities in Indonesia Considering the Factors of Weather-Induced Damages and Carbon Emissions

Ramadhani,

Sari,

Rifai

2024

AEJ

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This research discussed the Multi-Vehicle Capacitated Vehicle Routing Problem (MCVRP) in the rice commodity supply chain. This study considered the impact of weather conditions and carbon emissions on route decisions. These factors influenced travel time and rice quality, which can lead to delays, route changes, and increased supply chain costs. To account for weather conditions, the proposed model integrated historical weather data into route decisions. Additionally, the model incorporated carbon emissions as a significant factor in route decisions, aiming to reduce the environmental impact of transportation. This was achieved by considering vehicle fuel consumption and corresponding carbon emissions, optimizing route decisions to minimize the overall carbon footprint. The objective of this research was to develop a routing model that minimizes total costs while adhering to vehicle capacity constraints and customer delivery demands. Adaptive Large Neighborhood Search (ALNS) was proposed as an optimization method to solve the problem. Particularly, novel destroy and repair operators of ALNS were developed to specifically reduce the transportation cost, emission cost, and lost sales cost due to weather-induced damages. The results indicated that the proposed ALNS significantly decreased delivery expenses compared to the initial solution, achieving a 32% reduction in costs. The ALNS algorithm yielded superior outcomes compared to the standard LNS with lower objective and faster computing time. This research contributed to the development of sustainable supply chain practices in the rice commodity industry. The proposed approach provided a solution for MCVRP that considered weather conditions and carbon emissions while ensuring efficient commodity transportation.

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Section: Problem Formulationmentioning

confidence: 99%

Multi-Vehicle Capacitated Vehicle Routing Problem for Rice Commodities in Indonesia Considering the Factors of Weather-Induced Damages and Carbon Emissions

Ramadhani,

Sari,

Rifai

2024

AEJ

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“…With an increase in carbon emissions and the reduction in violation time windows, more vehicles and alternative fuel stations are used. Wen et al [25] have studied a multi-warehouse vehicle routing problem, established a model with the goals of including carbon emissions, fuel consumption, and vehicle rental and driver costs, and proposed an improved self-adaption large neighborhood search algorithm to efficiently solve the multi-depot green vehicle routing problem with time windows. Guo et al [26], considering the timeliness impact caused by traffic congestion, have established a time window model for the timely green vehicle routing problem of cold chain logistics, and proposed a two-order hybrid search algorithm.…”

Section: Literature Reviewmentioning

confidence: 99%

“…From a group perspective, the probability of self-adaption cross mutation can ensure better convergence of the algorithm while maintaining the diversity of the group. The self-adaption probability cross-and self-adaption mutation probability formulas are shown in Formulas (25) and (26), respectively.…”

Section: Improvement and Design Of Genetic Algorithmmentioning

confidence: 99%

Research on a Joint Distribution Vehicle Routing Problem Considering Simultaneous Pick-Up and Delivery under the Background of Carbon Trading

Ma,

2024

Sustainability

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In order to explore the positive impact of the joint distribution model on the reduction in logistics costs in small-scale logistics enterprises, considering the demand on enterprises for simultaneous pick-up and delivery, as well as the cost of carbon emissions, this study considers the vehicle routing problem of simultaneous pick-up and delivery under a joint distribution model. First of all, an independent distribution model and a joint distribution model including fixed transportation, variable transportation, time penalty, and carbon emissions costs are established; second, by adding the self-adaption cross-mutation probability and the destruction and repair mechanism in the large-scale neighborhood search algorithm, the genetic algorithm is improved to adapt to the solution of the model in this paper, and the effectiveness of the improved algorithm is verified and analyzed. It is found that the improved genetic algorithm is more advantageous than the original algorithm for solving the problems of both models designed in this paper. Finally, the improved genetic algorithm is used to solve the two models, and the results are compared and analyzed. It is found that the joint distribution model can reduce the total cost by 6.61% and the carbon emissions cost by 5.73%. Additionally, the impact of the carbon trading mechanism on the simultaneous pick-up and delivery vehicle routing problem under the joint distribution model is further explored. The results of this study prove that enterprises can effectively reduce costs, improve profits, reduce carbon emissions, and promote the sustainable development of logistics enterprises under the condition of joint distribution.

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“…To solve medium-and large-scale examples of this problem, this study adopts a heuristic algorithm that can be solved quicklythe ALNS algorithm. The ALNS algorithm was first proposed by Ropke and Pisinger [33], and it has been widely used to solve various VRPs in recent years ( [34][35][36][37]). Zhang et al [38] used ALNS to solve the multi-objective optimization problem of synchromodal transport.…”

Section: Proposed Algorithmsmentioning

confidence: 99%

An Adaptive Large Neighborhood Search Algorithm for Equipment Scheduling in the Railway Yard of an Automated Container Terminal

Chen,

Liu

2024

JMSE

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In container sea–rail combined transport, the railway yard in an automated container terminal (RYACT) is the link in the whole logistics transportation process, and its operation and scheduling efficiency directly affect the efficiency of logistics. To improve the equipment scheduling efficiency of an RYACT, this study examines the “RYACT–train” cooperative optimization problem in the mode of “unloading before loading” for train containers. A mixed-integer programming model with the objective of minimizing the maximum completion time of automated rail-mounted gantry crane (ARMG) tasks is established. An adaptive large neighborhood search (ALNS) algorithm and random search algorithm (RSA) are designed to solve the abovementioned problem, and the feasibility of the model and algorithm is verified by experiments. At the same time, the target value and calculation time of the model and algorithms are compared. The experimental results show that the model and the proposed algorithms are feasible and can effectively solve the “RYACT–train” cooperative optimization problem. The model only obtains the optimal solution of the “RYACT–train” cooperative scheduling problem with no more than 50 tasks within a limited time, and the ALNS algorithm can solve examples of various scales within a reasonable amount of time. The target value of the ALNS solution is smaller than that of the RSA solution.

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An adaptive large neighborhood search for the larger-scale multi depot green vehicle routing problem with time windows

Cited by 25 publications

References 49 publications

Multi-Vehicle Capacitated Vehicle Routing Problem for Rice Commodities in Indonesia Considering the Factors of Weather-Induced Damages and Carbon Emissions

Multi-Vehicle Capacitated Vehicle Routing Problem for Rice Commodities in Indonesia Considering the Factors of Weather-Induced Damages and Carbon Emissions

Research on a Joint Distribution Vehicle Routing Problem Considering Simultaneous Pick-Up and Delivery under the Background of Carbon Trading

An Adaptive Large Neighborhood Search Algorithm for Equipment Scheduling in the Railway Yard of an Automated Container Terminal

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