An intelligent green scheduling system for sustainable cold chain logistics

Shi, Yuhe; Lin, Yun; Lim, Ming K.; Tseng, Ming-Lang; Tan, Changlu; Li, Yan

doi:10.1016/j.eswa.2022.118378

Cited by 37 publications

(13 citation statements)

References 84 publications

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“…Numerous scholars have studied in-depth research on the issue of cold chain logistics vehicle routing problem (Shi et al, 2022b;Stellingwerf et al, 2021), with most aiming to minimize total cost (Chen et al, 2021a;Wang et al, 2021a). For example, designed a green vehicle routing model for cold chain logistics based on joint distribution with the goal of reducing overall cost.…”

Section: Cold Chain Logistics Vehicle Routing Problemmentioning

confidence: 99%

“…Numerous scholars have studied in-depth research on the issue of cold chain logistics vehicle routing problem (Shi et al ., 2022b; Stellingwerf et al ., 2021), with most aiming to minimize total cost (Chen et al. , 2021a; Wang et al ., 2021a).…”

Section: Literature Reviewmentioning

confidence: 99%

“…Therefore, it is crucial to consider the carbon emissions produced by road transportation. In this context, cold chain logistics, as an important component of road transportation, should also be paid attention to (Shi et al, 2022b). Cold chain logistics produces more carbon emissions than normal logistics because it requires more fuel to keep a cold environment (Chen et al, 2021a).…”

Section: Introductionmentioning

confidence: 99%

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An electric vehicle routing model with charging stations consideration for sustainable logistics

Li,

Lim,

Xiong

et al. 2023

IMDS

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PurposeRecently, electric vehicles have been widely used in the cold chain logistics sector to reduce the effects of excessive energy consumption and to support environmental friendliness. Considering the limited battery capacity of electric vehicles, it is vital to optimize battery charging during the distribution process.Design/methodology/approachThis study establishes an electric vehicle routing model for cold chain logistics with charging stations, which will integrate multiple distribution centers to achieve sustainable logistics. The suggested optimization model aimed at minimizing the overall cost of cold chain logistics, which incorporates fixed, damage, refrigeration, penalty, queuing, energy and carbon emission costs. In addition, the proposed model takes into accounts factors such as time-varying speed, time-varying electricity price, energy consumption and queuing at the charging station. In the proposed model, a hybrid crow search algorithm (CSA), which combines opposition-based learning (OBL) and taboo search (TS), is developed for optimization purposes. To evaluate the model, algorithms and model experiments are conducted based on a real case in Chongqing, China.FindingsThe result of algorithm experiments illustrate that hybrid CSA is effective in terms of both solution quality and speed compared to genetic algorithm (GA) and particle swarm optimization (PSO). In addition, the model experiments highlight the benefits of joint distribution over individual distribution in reducing costs and carbon emissions.Research limitations/implicationsThe optimization model of cold chain logistics routes based on electric vehicles provides a reference for managers to develop distribution plans, which contributes to the development of sustainable logistics.Originality/valueIn prior studies, many scholars have conducted related research on the subject of cold chain logistics vehicle routing problems and electric vehicle routing problems separately, but few have merged the above two subjects. In response, this study innovatively designs an electric vehicle routing model for cold chain logistics with consideration of time-varying speeds, time-varying electricity prices, energy consumption and queues at charging stations to make it consistent with the real world.

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Section: Cold Chain Logistics Vehicle Routing Problemmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An electric vehicle routing model with charging stations consideration for sustainable logistics

Li,

Lim,

Xiong

et al. 2023

IMDS

Self Cite

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“…Along with this trend, people have begun to pay attention to environmental protection and energy conservation in the logistics and warehousing industry, and gradually accepted the concept of green warehousing [11][12][13][14][15]. Implementing green warehousing management can reduce the environmental pollution caused by warehousing while ensuring the quality and quantity of the stored goods, and improve the various problems of regular logistics storage space such as heavy environmental pollution, high energy consumption, large cargo loss, poor thermal environment and high transportation costs [16][17][18][19][20][21]. Among these problems, high temperature in summer is the most prominent one.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Heat and Moisture Transfer and Thermal Comfort in Green Logistics Storage Space

Wang¹,

Lu²

2022

IJHT

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Regular logistics storage spaces suffer a very high temperature during summer. To build a green logistics storage space, it is truly necessary to optimize the thermal environment in summer. At present, there are few related studies on the energy consumption, thermal environment and human comfort of green logistics storage spaces. Therefore, this paper analyzes the heat and moisture transfer in and studies the impacts of the thermal environment of green logistics storage space. Based on the survey results, a coupled heat-moisture transfer model of green logistics storage space was constructed, which consists of three parts - the envelope structure, the hot and humid indoor environment, and the heating, ventilation and air conditioning (HVAC) system. Based on the idea of linear regression, a model was established to predict human body’s subjective thermal sensation in green logistics storage space. The experiment showed the analysis results of heat and moisture transfer and thermal comfort in green logistics storage space, and verified the effectiveness of the proposed model.

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“…Environmental impact is not considered as a single optimization criterion in any of the papers but is present as one of the criteria in papers [1][2][3][4][5][6][7][8][9][22][23][24][25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41]66,[73][74][75][76].…”

mentioning

confidence: 99%

Optimizing Utilization of Transport Capacities in the Cold Chain by Introducing Dynamic Allocation of Semi-Trailers

Stanković,

Pereglin,

Erdelić

2023

Logistics

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Background: Road transport companies utilize transport capacities as fixed compositions of tractors and semi-trailers, while the possibility of exchanging semi-trailers is considered ad hoc, after some unforeseen circumstances emerge on the route. Such an approach is a limiting factor in achieving optimal utilization of transport capacities, and consequently affects profitability. We proposed a new concept of vehicle fleet management where semi-trailers would not be permanently assigned to the tractors, but could be dynamically reassigned, to utilize optimally the vehicle fleet, on considering the planned itinerary, the driver’s working hours, and traffic conditions. Methods: We set the key performance indicators and developed a prototype application based on the concept of dynamic semi-trailer allocation. We simulated the use of the prototype application on the historical data collected in the case study on one of the leading transport companies in the cold chain, and evaluated the benefits that may be achieved thereof. Results: Simulation showed that implementing the proposed concept enabled the reduction of the vehicle workdays spent on-the-route, the reduction of the number of vehicle compositions needed to handle the transport demand, and improved the quality of service. Conclusions: The proposed concept is beneficial for transport companies that operate large vehicle fleets on long-haul routes, with several transport orders per route. The prototype application may be the basis for developing a fully functional application that can be integrated into the fleet management system.

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An intelligent green scheduling system for sustainable cold chain logistics

Cited by 37 publications

References 84 publications

An electric vehicle routing model with charging stations consideration for sustainable logistics

An electric vehicle routing model with charging stations consideration for sustainable logistics

Analysis of Heat and Moisture Transfer and Thermal Comfort in Green Logistics Storage Space

Optimizing Utilization of Transport Capacities in the Cold Chain by Introducing Dynamic Allocation of Semi-Trailers

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