Research

19 pages, 3034 KiB

Open AccessArticle

Impact of Transportation Costs on the Establishment of an Industrial Symbiosis Network

by Mohamed Amine Anane, Faezeh Bagheri, Elvezia Maria Cepolina and Flavio Tonelli

Sustainability 2023, 15(22), 15701; https://doi.org/10.3390/su152215701 - 07 Nov 2023

Viewed by 719

The challenges related to natural resource depletion and environmental issues stimulate businesses to look for solutions to overcome them. One of the leading strategies that have emerged from the practical implementation of the circular economy concept is industrial symbiosis, which aims to reduce [...] Read more.

The challenges related to natural resource depletion and environmental issues stimulate businesses to look for solutions to overcome them. One of the leading strategies that have emerged from the practical implementation of the circular economy concept is industrial symbiosis, which aims to reduce material extraction and consumption by using the waste (co-product) of one company as input for production processes of another company. This study aims to provide a more profound insight into industrial symbiosis (IS) modeling by considering the transport system impact. To this end, a hybrid approach based on agent-based modeling and system dynamics is presented to comprehensively capture the complexity of interactions between companies and their related impacts on transportation. A case study and numerical example are discussed to validate the proposed approach and related model. The results demonstrate that the development of IS, as expected, is significantly influenced by the transport system. Full article

(This article belongs to the Special Issue Green Logistics and Intelligent Transportation)

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25 pages, 4754 KiB

Open AccessArticle

A Simulation-Based Experimental Design for Analyzing Energy Consumption and Order Tardiness in Warehousing Systems

by Hyun-woo Jeon, Ahmad Ebrahimi and Ga-hyun Lee

Sustainability 2023, 15(20), 14891; https://doi.org/10.3390/su152014891 - 15 Oct 2023

Viewed by 833

Abstract

For warehouses to be more sustainable and cost-effective, it is essential to consider energy consumption (EC) and order tardiness (OT) together in evaluating warehouse activities since improving both EC and OT at the same time is very demanding. While existing studies try to [...] Read more.

For warehouses to be more sustainable and cost-effective, it is essential to consider energy consumption (EC) and order tardiness (OT) together in evaluating warehouse activities since improving both EC and OT at the same time is very demanding. While existing studies try to improve EC and OT, the current studies consider only either a reserve area or a forward area between the two major warehouse areas. Thus, this study proposes a simulation-based approach to assessing EC and OT when reserve and forward areas are considered together in one framework for different configurations of five important warehousing parameters: (i) number of forklifts, (ii) number of storage/retrieval (S/R) machines, (iii) number of automated storage/retrieval systems (AS/RS) input/output (I/O) points, (iv) order size, and (v) proportions of order flows through a reserve or forward area. In particular, we use real forklift movement and energy data for our simulation models to provide a more realistic analysis. By building the simulation model with the 2⁵ full factorial experimental design, we analyze the results with analysis of variance (ANOVA). The resulting Pareto-optimal solutions show that less traffic flows through a reserve area can help improve both EC and OT while other factors have smaller or limited effects on the two responses. Also, the order flow factor has the largest effect on EC while order size has the largest effect on OT. The results from this study can help warehouse operators make informed decisions in considering and finding a trade-off between sustainability and customer satisfaction. Full article

(This article belongs to the Special Issue Green Logistics and Intelligent Transportation)

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15 pages, 786 KiB

Open AccessArticle

Online Delivery Problem for Hybrid Truck–Drone System with Independent and Truck-Carried Drones

by Mengyuan Gou and Haiyan Yu

Sustainability 2023, 15(2), 1584; https://doi.org/10.3390/su15021584 - 13 Jan 2023

Viewed by 1433

Abstract

Considering real-time requests and multiple truck–drone delivery modes, we propose an online delivery problem using a truck and some drones, which form a hybrid truck–drone delivery collaboration system comprising independent and truck-carried drones. Considering this problem, we focus on how to schedule the [...] Read more.

Considering real-time requests and multiple truck–drone delivery modes, we propose an online delivery problem using a truck and some drones, which form a hybrid truck–drone delivery collaboration system comprising independent and truck-carried drones. Considering this problem, we focus on how to schedule the vehicles to serve real-time requests, with the objective of minimizing the time of the latest vehicle’s return to the delivery station. First, we proved the lower bound of this problem to be 1.5. Second, we designed an online re-planning algorithm and proved its competitive ratio to be 2.5. As the online re-planning algorithm invokes an offline algorithm, an offline model was established, and an offline drone priority algorithm was designed. Then, we verified the effectiveness of the offline algorithm by comparing it with the CPLEX solution, and the stability of the online re-planning algorithm with different input parameters was studied through MATLAB simulation. Finally, the minimal latest time saving was calculated by comparing the hybrid truck–drone collaboration system with a truck-only delivery system. This research provides theoretical support for addressing the hybrid truck–drone delivery problem. Full article

(This article belongs to the Special Issue Green Logistics and Intelligent Transportation)

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21 pages, 754 KiB

Open AccessArticle

Enhancing Food Supply Chain in Green Logistics with Multi-Level Processing Strategy under Disruptions

by Ming Liu, Hao Tang, Yunfeng Wang, Ruixi Li, Yi Liu, Xin Liu, Yaqian Wang, Yiyang Wu, Yu Wu and Zhijun Sun

Sustainability 2023, 15(2), 917; https://doi.org/10.3390/su15020917 - 04 Jan 2023

Cited by 3 | Viewed by 1460

Abstract

Food supply chains (FSCs) have long been exposed to environmental variability and shock events caused by various economic, political, and infrastructural factors. The outbreak of the COVID-19 pandemic has further exposed and identified the vulnerability of FSCs, and promoted integrated optimization approaches for [...] Read more.

Food supply chains (FSCs) have long been exposed to environmental variability and shock events caused by various economic, political, and infrastructural factors. The outbreak of the COVID-19 pandemic has further exposed and identified the vulnerability of FSCs, and promoted integrated optimization approaches for building resilience. However, existing works focusing on general supply chains (SCs) and FSCs have not been fully aware of the distinct characteristics of FSCs in green logistics, i.e., the expiration of fresh products. In reality, perishable food materials can be processed into products of different processing levels (i.e., multi-level processing) for longer shelf lives, which can serve as a timely and economic strategy to increase safety stocks for mitigating disruption risks. Motivated by this fact, we study the problem of enhancing FSC with a multi-level processing strategy. An integrated location, inventory, and distribution planning model for a multi-echelon FSC under COVID-19-related disruptions is formulated to maximize the total profit over a finite planning horizon. Specifically, a two-stage stochastic programming model is presented to hedge against disruption risks, where scenarios are generated to characterize geographical impact induced by source-region disruptions. For small-scale problems, the model can be solved with commercial solvers. To exactly and efficiently solve the large-scale instances, we design an integer L-shaped method. Numerical experiments are conducted on a case study and randomly generated instances to show the efficiency of our model and solution method. Based on the case study, managerial insights are drawn. Full article

(This article belongs to the Special Issue Green Logistics and Intelligent Transportation)

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22 pages, 1157 KiB

Open AccessArticle

Green Airline-Fleet Assignment with Uncertain Passenger Demand and Fuel Price

by Ming Liu, Yueyu Ding, Lihua Sun, Runchun Zhang, Yue Dong, Zihan Zhao, Yiting Wang and Chaoran Liu

Sustainability 2023, 15(2), 899; https://doi.org/10.3390/su15020899 - 04 Jan 2023

Cited by 2 | Viewed by 1617

Abstract

Although air transport contributes to globalization, airline emissions have attracted focus in green logistics. In this work, we investigate the airline-fleet assignment problem from a risk-averse perspective in which uncertain demand and fuel price are considered simultaneously. The objective is to maximise the [...] Read more.

Although air transport contributes to globalization, airline emissions have attracted focus in green logistics. In this work, we investigate the airline-fleet assignment problem from a risk-averse perspective in which uncertain demand and fuel price are considered simultaneously. The objective is to maximise the total profit in a risk-averse fashion, i.e., the weighted sum of the expected profit and the conditional value at risk of profit. An appropriate assignment can reduce fuel use and carbon dioxide emissions. For the problem, a two-stage stochastic programming model is constructed. The first stage consists of assigning aircraft families to flight legs, while the second stage determines specific aircraft deployment with the realized information. To solve the problem, a sample average approximation (SAA) approach is firstly applied. An efficient string-based heuristic is, further, developed. Numerical experiments are conducted and sensitivity analysis is performed. The results show the efficiency of the proposed heuristic and managerial insights are drawn. Full article

(This article belongs to the Special Issue Green Logistics and Intelligent Transportation)

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18 pages, 2302 KiB

Open AccessArticle

The Effect of Consumer Sentiment on Manufacturers’ Green Technology Innovation: A RDEU Evolutionary Game Model

by Hongbo Guo, Mengtong Lu and Lili Ding

Sustainability 2023, 15(1), 706; https://doi.org/10.3390/su15010706 - 30 Dec 2022

Cited by 3 | Viewed by 1421

Abstract

In the information era, the fluctuation of consumer sentiments plays a key role in the green technology innovation of manufacturers. This paper introduces RDEU theory to the evolutionary game model to analyze the existence of equilibrium under different sentiment states. Then, the model [...] Read more.

In the information era, the fluctuation of consumer sentiments plays a key role in the green technology innovation of manufacturers. This paper introduces RDEU theory to the evolutionary game model to analyze the existence of equilibrium under different sentiment states. Then, the model is numerically simulated to study the influence of sentiments on the participants’ strategies. The results indicate that under different sentiment states green technology innovation and green purchasing behavior present different evolutionary trajectories. The main conclusions are as follows: (1) When both parties have no sentiments, there is a stable equilibrium point, suggesting customers are willing to purchase green products and manufacturers choose green technology innovation strategies. (2) When both parties have sentiments, the rising consumer boycott sentiment will hinder optimistic manufacturers from choosing green technology innovation strategies. Furthermore, the rising support sentiment of the consumer promotes optimistic manufacturers’ green technology innovations, and the more manufacturers deviate from the rational state, the more likely they are to maintain the current production mode. (3) When only one party has a sentiment, the manufacturer’s rationality plays a more important role in promoting green technology innovation than the consumer’s rationality. Based on the above conclusions, this paper proposes some sentiment guidance strategies that are conducive to green production and consumption. This study provides a new perspective and theoretical guidance for studying the behavior of green supply chain members to promote the development of green economy circulation. Full article

(This article belongs to the Special Issue Green Logistics and Intelligent Transportation)

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14 pages, 452 KiB

Open AccessArticle

Coordinated Distribution or Client Introduce? Analysis of Energy Conservation and Emission Reduction in Canadian Logistics Enterprises

by Yuntao Bai, Yuan Gao, Delong Li and Dehai Liu

Sustainability 2022, 14(24), 16979; https://doi.org/10.3390/su142416979 - 18 Dec 2022

Cited by 6 | Viewed by 1111

Abstract

Due to the large area and small population of Canada, the efficiency of logistics enterprises is low, and each logistics enterprise needs to cooperate to save energy and reduce emissions. Considering that each logistics enterprise can realize the maximization of its own benefit [...] Read more.

Due to the large area and small population of Canada, the efficiency of logistics enterprises is low, and each logistics enterprise needs to cooperate to save energy and reduce emissions. Considering that each logistics enterprise can realize the maximization of its own benefit by controlling the distribution volume and the input of facilities. In this article, the differential game model of individual distribution, coordinated distribution and paid introduction of customers for each logistics enterprise is constructed, the balanced distribution volume, capital input and social welfare functions of each logistics enterprise under the three modes are obtained, and the applicable conditions of various distribution cooperation channels are compared. The research results show that if the organizational cost between logistics enterprises is greater than the communication cost, the benefits of large-scale logistics enterprises under the introduction customer mode are greater than those under the collaborative distribution mode. However, only the communication cost and organizational cost are relatively small, and the profit of small-scale logistics enterprises under the introduction of the customer mode is smaller than that under the collaborative distribution mode. Full article

(This article belongs to the Special Issue Green Logistics and Intelligent Transportation)

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21 pages, 3154 KiB

Open AccessArticle

Entropy-Maximization-Based Customer Order Allocation of Clothing Production Enterprises in the Sharing Economy

by Feifeng Zheng, Chunle Kang, Qinrui Song and Ming Liu

Sustainability 2022, 14(22), 15106; https://doi.org/10.3390/su142215106 - 15 Nov 2022

Cited by 1 | Viewed by 1058

Abstract

With the rapid development of the sharing economy, more and more platform operators apply the sharing concept in manufacturing, which increases the efficiency of assets utilization. Considering the apparel industry, clothing enterprises or manufacturers may share their excess orders between each other via [...] Read more.

With the rapid development of the sharing economy, more and more platform operators apply the sharing concept in manufacturing, which increases the efficiency of assets utilization. Considering the apparel industry, clothing enterprises or manufacturers may share their excess orders between each other via a manufacturing cloud platform. Under the traditional production mode, manufacturers focus on processing their individual orders. There may be a coexistence of insufficient and surplus production capabilities. Some manufacturers cannot meet their customer demands due to limited capabilities and some orders have to be rejected, while some other manufacturers may have excess capacities with insufficient demands. It results in loss of revenue, and it is not conducive to maintaining a good customer relationship. In this paper, we consider a shared system with multiple manufacturers that produce homogeneous products, and the manufacturers in the shared system can share customer orders with each other. Once any manufacturer cannot fulfill all of its orders, the unsatisfied ones will be shared with other manufacturers that have surplus capacities with the aim of improving the balance of resource utilization and risk resistance of all manufacturers on the platform. The entropy maximization theory is mainly adopted to facilitate the formulation of the objective function. We apply a Taylor expansion to reformulate the objective function and construct a mixed-integer quadratic programming (MIQP) model. We employ off-the-shelf solvers to solve small-scale problems, and also propose a two-stage constructive heuristic algorithm to solve large-scale problems. Numerical experiments are conducted to demonstrate the efficiency of the algorithm. Full article

(This article belongs to the Special Issue Green Logistics and Intelligent Transportation)

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