Multi-Objective Sustainable Closed-Loop Supply Chain Network Design Considering Multiple Products with Different Quality Levels

Soon, Amirhossein; Heidari, Ali; Khalilzadeh, Mohammad; Antuchevičienė, Jurgita; Zavadskas, Edmundas Kazimieras; Zahedi, Farbod

doi:10.3390/systems10040094

Cited by 13 publications

(5 citation statements)

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“…In the time dimension, the robustness of a logistics network can be evaluated by the time response of the logistics system [28], which is the maximum possible damage according to the residual connectivity after a disruption [29]. A good robustness should have a good time response performance in multiple products [30], collaborative distribution [31] and malicious attacks [32]. A robust logistics network may diminish the loss of disruptions or the number of disruption nodes [33].…”

Section: Literature Reviewmentioning

confidence: 99%

Design a Robust Logistics Network with an Artificial Physarum Swarm Algorithm

et al. 2022

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The robust optimization of logistics networks can improve the ability to provide sustainable service and business sustainability after uncertain disruptions. The existing works on the robust design of logistics networks insisted that it is very difficult to build a robust network topology, and this kind of optimization problem is an NP-hard problem that cannot be easily solved. In nature, Physarum often needs to build a robust and efficient topological network to complete the foraging process. Recently, some researchers used Physarum to build a robust transportation network in professional biological laboratories and received a good performance. Inspired by the foraging behavior of natural Physarum, we proposed a novel artificial Physarum swarm system to optimize the logistics network robustness just on a personal computer. In our study, first, the robustness optimization problem of a logistics network is described as a topology optimization model based on graph theory, and four robustness indicators are proposed to build a multi-objective robustness function of logistics network topology, including the relative robustness, the betweenness robustness, the edge robustness and the closeness robustness. Second, an artificial Physarum swarm system is developed to simulate the foraging behavior of a natural Physarum swarm to solve this kind of complex robust optimization problem. The proposed artificial Physarum swarm system can search for optimal solutions by expansion and contraction operations and the exchange of information with each other through a self-learning experience and neighbor-learning experiences. The plasmodium of Physarum forms the edges, and the external food sources simulate the logistics nodes. Third, an experimental example is designed on the basis of Mexico City to verify the proposed method, and the results reveal that the artificial Physarum swarm system can help us effectively improve the logistics network robustness under disruptions and receive a better performance than natural Physarum. The article may be helpful for both theory and practice to explore the robust optimization in logistics operation and provide engineers with an opportunity to resist logistics disruptions and risk loss by a novel artificial intelligence tool.

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Section: Literature Reviewmentioning

confidence: 99%

Design a Robust Logistics Network with an Artificial Physarum Swarm Algorithm

et al. 2022

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“…Soon et al proposed a robust multi-objective mathematical model for a sustainable closed-loop supply chain network. The network model can meet different types of customer needs and has different quality levels [18]. Although many outstanding achievements have been made in hierarchical scheduling and production planning of complex supply chain systems, there are still some thorny problems to be solved.…”

Section: Introductionmentioning

confidence: 99%

Guarantee Stability of Supply Chain with Dual Channels under Supply Failure of Goods

Fan

2023

Sustainability

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The supply chain is an extremely important and complex system, which is widely related to the social system and the management system. The hierarchical scheduling and production planning of a dynamic supply chain can enable enterprises in the supply chain to obtain, and maintain, stable and lasting competitive advantages; thus, improving the overall competitiveness of the supply chain. Simultaneously, research on supply chains is also a hotspot in system engineering. At present, research on complex supply chain systems with dual channels is insufficient, and analysis of dynamic supply chains with supply failure of goods is rare. In the epidemic era, dynamic supply chain management was affected by the epidemic and became a very challenging topic. The control of the supply chain system under the impact of an epidemic situation is particularly important. This paper focused on H∞ the fault-tolerant control of a complex supply chain system with dual channels. First, from the perspective of engineering practice and green production, we established a new green supply chain model. This supply chain model includes the dual-channel supply of goods and also considers the supply failure of goods. At the same time, production delay and supply delay are also considered in this model. Second, a supply scheduling scheme was designed through cybernetics to ensure the stability of a supply chain with dual channels under supply failure of goods, and we completed supply chain management. Finally, the effectiveness of our results was verified by specific Chinese enterprise data.

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“…Therefore, distribution system optimization is one of the main Solving electric vehicle's routing problem goals of logistics companies. Evidence shows that the optimization of distribution and service systems has played a major role in significantly reducing transportation costs (Toth and Vigo, 2002;Soon et al, 2022). On the other hand, in terms of customer satisfaction, it can be said that coping with the loss of only 5% of customers, results in a 25%-85% increase in the annual revenue of the distribution and service systems based on the type of industry.…”

Section: Introductionmentioning

confidence: 99%

A hybrid metaheuristic approach for solving a bi-objective capacitated electric vehicle routing problem with time windows and partial recharging

Zahedi

Kia

Khalilzadeh³

2023

JAMR

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PurposeThe vehicle routing problem (VRP) has been widely investigated during last decades to reduce logistics costs and improve service level. In addition, many researchers have realized the importance of green logistic system design in decreasing environmental pollution and achieving sustainable development.Design/methodology/approachIn this paper, a bi-objective mathematical model is developed for the capacitated electric VRP with time windows and partial recharge. The first objective deals with minimizing the route to reduce the costs related to vehicles, while the second objective minimizes the delay of arrival vehicles to depots based on the soft time window. A hybrid metaheuristic algorithm including non-dominated sorting genetic algorithm (NSGA-II) and teaching-learning-based optimization (TLBO), called NSGA-II-TLBO, is proposed for solving this problem. The Taguchi method is used to adjust the parameters of algorithms. Several numerical instances in different sizes are solved and the performance of the proposed algorithm is compared to NSGA-II and multi-objective simulated annealing (MOSA) as two well-known algorithms based on the five indexes including time, mean ideal distance (MID), diversity, spacing and the Rate of Achievement to two objectives Simultaneously (RAS).FindingsThe results demonstrate that the hybrid algorithm outperforms terms of spacing and RAS indexes with p-value <0.04. However, MOSA and NSGA-II algorithms have better performance in terms of central processing unit (CPU) time index. In addition, there is no meaningful difference between the algorithms in terms of MID and diversity indexes. Finally, the impacts of changing the parameters of the model on the results are investigated by performing sensitivity analysis.Originality/valueIn this research, an environment-friendly transportation system is addressed by presenting a bi-objective mathematical model for the routing problem of an electric capacitated vehicle considering the time windows with the possibility of recharging.

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Multi-Objective Sustainable Closed-Loop Supply Chain Network Design Considering Multiple Products with Different Quality Levels

Cited by 13 publications

References 50 publications

Design a Robust Logistics Network with an Artificial Physarum Swarm Algorithm

Design a Robust Logistics Network with an Artificial Physarum Swarm Algorithm

Guarantee Stability of Supply Chain with Dual Channels under Supply Failure of Goods

A hybrid metaheuristic approach for solving a bi-objective capacitated electric vehicle routing problem with time windows and partial recharging

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