scholarly journals Designing a Resilient and Sustainable Logistics Network under Epidemic Disruptions and Demand Uncertainty

2021 ◽  
Vol 13 (24) ◽  
pp. 14053
Author(s):  
Aymen Aloui ◽  
Nadia Hamani ◽  
Laurent Delahoche

To face the new challenges caused by modern industry, logistics operations managers need to focus more on integrating sustainability goals, adapt to unexpected disruptions and find new strategies and models for logistics management. The COVID-19 pandemic has proven that unforeseen fragilities, negatively affecting the supply chain performance, can arise rapidly, and logistics systems may confront unprecedented vulnerabilities regarding network structure disruption and high demand fluctuations. The existing studies on a resilient logistics network design did not sufficiently consider sustainability aspects. In fact, they mainly addressed the independent planning of decision-making problems with economic objectives. To fill this research gap, this paper concentrates on the design of resilient and sustainable logistics networks under epidemic disruption and demand uncertainty. A two-stage stochastic mixed integer programming model is proposed to integrate key decisions of location–allocation, inventory and routing planning. Moreover, epidemic disruptions and demand uncertainty are incorporated through plausible scenarios using a Monte Carlo simulation. In addition, two resiliency strategies, namely, capacity augmentation and logistics collaboration, are included into the basic model in order to improve the resilience and the sustainability of a logistics chain network. Finally, numerical examples are presented to validate the proposed approach, evaluate the performance of the different design models and provide managerial insights. The obtained results show that the integration of two design strategies improves resilience and sustainability.

2020 ◽  
Vol 54 (5) ◽  
pp. 1288-1306 ◽  
Author(s):  
Yadong Wang ◽  
Qiang Meng

Semi-liner shipping transports various types of cargo, such as containers, break-bulk cargo, and heavy-lift project cargo, between different ports. Similar to liner shipping, semi-liner shipping publishes shipping routes for customers’ reference. However, it does not strictly follow the published route and usually makes some adjustments for each ship voyage by adding some port calls to transport more cargo considering the excess ship capacity. This study first proposes the semi-liner shipping service design (SLSSD) problem that aims to maximize the shipping profit by determining a shipping route subject to the potential adjustments. The proposed SLSSD problem is subsequently formulated as a two-stage stochastic mixed integer programming model with integer recourse variables. The first stage determines the visit sequence of a set of compulsory ports under shipping demand uncertainty. The second stage decides whether to add or remove some ports in the route in view of the realized shipping demand for each ship voyage. To effectively solve the model, two decomposition methods are developed, namely, the stage decomposition method and the scenario decomposition method, that decompose the problem by stage and demand scenario, respectively. In addition, two novel acceleration techniques are also provided to expedite the scenario decomposition method. Numerical experiments reveal satisfactory efficiency of these two methods to solve the semi-liner shipping service design problem, especially the scenario decomposition method, which is generally better than the stage decomposition method and can be thousands of times faster than the classic branch-and-cut algorithm.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Anton Ochoa Bique ◽  
Leonardo K. K. Maia ◽  
Ignacio E. Grossmann ◽  
Edwin Zondervan

Abstract A strategy for the design of a hydrogen supply chain (HSC) network in Germany incorporating the uncertainty in the hydrogen demand is proposed. Based on univariate sensitivity analysis, uncertainty in hydrogen demand has a very strong impact on the overall system costs. Therefore we consider a scenario tree for a stochastic mixed integer linear programming model that incorporates the uncertainty in the hydrogen demand. The model consists of two configurations, which are analyzed and compared to each other according to production types: water electrolysis versus steam methane reforming. Each configuration has a cost minimization target. The concept of value of stochastic solution (VSS) is used to evaluate the stochastic optimization results and compare them to their deterministic counterpart. The VSS of each configuration shows significant benefits of a stochastic optimization approach for the model presented in this study, corresponding up to 26% of infrastructure investments savings.


2019 ◽  
Vol 11 (11) ◽  
pp. 3127 ◽  
Author(s):  
Tarik Chargui ◽  
Abdelghani Bekrar ◽  
Mohamed Reghioui ◽  
Damien Trentesaux

In the context of supply chain sustainability, Physical Internet (PI or π ) was presented as an innovative concept to create a global sustainable logistics system. One of the main components of the Physical Internet paradigm consists in encapsulating products in modular and standardized PI-containers able to move via PI-nodes (such as PI-hubs) using collaborative routing protocols. This study focuses on optimizing operations occurring in a Rail–Road PI-Hub cross-docking terminal. The problem consists of scheduling outbound trucks at the docks and the routing of PI-containers in the PI-sorter zone of the Rail–Road PI-Hub cross-docking terminal. The first objective is to minimize the energy consumption of the PI-conveyors used to transfer PI-containers from the train to the outbound trucks. The second objective is to minimize the cost of using outbound trucks for different destinations. The problem is formulated as a Multi-Objective Mixed-Integer Programming model (MO-MIP) and solved with CPLEX solver using Lexicographic Goal Programming. Then, two multi-objective hybrid meta-heuristics are proposed to enhance the computational time as CPLEX was time consuming, especially for large size instances: Multi-Objective Variable Neighborhood Search hybridized with Simulated Annealing (MO-VNSSA) and with a Tabu Search (MO-VNSTS). The two meta-heuristics are tested on 32 instances (27 small instances and 5 large instances). CPLEX found the optimal solutions for only 23 instances. Results show that the proposed MO-VNSSA and MO-VNSTS are able to find optimal and near optimal solutions within a reasonable computational time. The two meta-heuristics found optimal solutions for the first objective in all the instances. For the second objective, MO-VNSSA and MO-VNSTS found optimal solutions for 7 instances. In order to evaluate the results for the second objective, a one way analysis of variance ANOVA was performed.


2020 ◽  
Vol 12 (21) ◽  
pp. 9147
Author(s):  
Hairui Wei ◽  
Anlin Li ◽  
Nana Jia

As a new mode of transportation, the underground logistics system (ULS) has become one of the solutions to the problems of environmental pollution and traffic congestion. Considering the environmental and economic factors in urban logistics, this paper conducts comprehensive design and optimization research on the network nodes and passages of urban underground logistics and proposes a relatively complete framework for a sustainable underground logistics network. A hybrid method is proposed, which includes the set cover model used to perform the first location of urban underground logistics nodes, the fuzzy clustering method applied to classify the located logistics nodes into the first-level and second-level nodes considering the congestion in different urban areas of the city and a mixed integer programming model proposed to optimize and design the underground logistics passage to find optimal passage parameters at every underground logistics node. Based on the above hybrid method, a sustainable underground logistics network framework including all-levels logistics nodes and passages is formed, with a subdistrict of Nanjing as a case study. The discussion of results shows that this underground logistics network framework proposal is very effective in reducing logistics time cost, exhaust emission and congestion cost. It provides support for decisions in the design and development of urban sustainable underground logistics networks.


2019 ◽  
Vol 12 (2) ◽  
pp. 356
Author(s):  
Jingjing Hu ◽  
Youfang Huang

Purpose: The overstocked goods flow in the hub of hub-and-spoke logistics network should be disposed of in time, to reduce delay loss and improve the utilization rate of logistics network resources. The problem we need to solve is to let logistics network cooperate by sharing network resources to shunt goods from one hub-and-spoke network to another hub-and-spoke network.Design/methodology/approach: This paper proposes the hub shunting cooperation between two hub-and-spoke networks. Firstly, a hybrid integer programming model was established to describe the problem, and then a multi-layer genetic algorithm was designed to solve it and two hub-and-spoke networks are expressed by different gene segments encoded by genes. The network data of two third-party logistics companies in southern and northern China are used for example analysis at the last step. Findings: The hub-and-spoke networks of the two companies were constructed simultaneously. The transfer cost coefficient between two networks and the volume of cargo flow in the network have an impact on the computation of hubs that needed to be shunt and the corresponding cooperation hubs in the other network.Originality/value: Previous researches on hub-and-spoke logistics network focus on one logistics network, while we study the cooperation and interaction between two hub-and-spoke networks. It shows that two hub-and-spoke network can cooperate across the network to shunt the goods in the hub and improve the operation efficiency of the logistics network. 


Logistics ◽  
2021 ◽  
Vol 5 (3) ◽  
pp. 61
Author(s):  
Dhirendra Prajapati ◽  
M. Manoj Kumar ◽  
Saurabh Pratap ◽  
H. Chelladurai ◽  
Mohd Zuhair

In the recent era, the rapidly increasing trend of e-commerce business creates opportunities for logistics service providers to grow globally. With this growth, the concern regarding the implementation of sustainability in logistic networks has received attention in recent years. Thus, in this work, we have focused on the vehicle routing problem (VRP) to deliver the products in a lesser time horizon with driver safety concern considerations in business (B2B) e-commerce platforms. We proposed a sustainable logistics network that captures the complexities of suppliers, retailers, and logistics service providers. A mixed-integer nonlinear programming (MINLP) approach is applied to formulate a model to minimize total time associated with order processing, handling, packaging, shipping, and vehicle maintenance. Branch-and-bound algorithms in the LINGO optimization tool and genetic algorithm (GA) are used to solve the formulated mathematical model. The computational experiments are performed in eight different case scenarios (small-sized problem to large-sized problem) to validate the model.


2020 ◽  
Vol 27 (4) ◽  
Author(s):  
Bruno Vinícius Ribeiro Furlanetto ◽  
Fernando Augusto Silva Marins ◽  
Aneirson Francisco da Silva ◽  
Cristiane Maria Defalque

Abstract This article analyzes the impacts of operational and tax changes in a logistics network, considering the location of facilities and the following taxes: the Brazilian State Excise Tax on Circulation of Goods and Services, the Import Duty, the Brazilian State Excise Tax in Tax Substitution, the Social Integration Program, the Contribution for the Financing of Social Security and the Brazilian Federal Excise Tax on Industrialized Products. The influence of incorporations and outsourcing of distribution services in solving global localization issues concerning various links in a chain suplly has also been considered. The problem was modeled and solved by the GAMS modeling language using Solver CPLEX. The proposed Mixed Integer Linear Programming model minimizes operating costs taking into account tax benefits and the best use of the credits related to the Tax on Circulation of Goods and Services of a multiproduct network. A real application involving a company in the animal feed production sector was developed. The results showed that the model allowed to evaluate conveniently how the choice of the facilities and the characteristics of the product flows impacted the overall costs of the system. The results also evidenced the need to make decisions based on the existing tax structure, since the scenarios without tax optimization generated substantial losses to the companies. This information added quality to the manager of the company studied.


2020 ◽  
Vol 12 (17) ◽  
pp. 6983
Author(s):  
Snežana Tadić ◽  
Mladen Krstić ◽  
Violeta Roso ◽  
Nikolina Brnjac

Globalization and decentralization of production generate the intensive growth of goods and transport flows, mostly performed by the maritime transport. Ports, as the main nodes in the global logistics networks, are becoming congested, space for their expansion limited, and traffic in their hinterland congested. As a solution to these and many other hinterland-transport-related problems stands out the development of dry port (DP) terminals. Selection of their location is one of the most important strategic decisions on which depends their competitiveness in the market and the functionality of the logistics network. Accordingly, the evaluation and selection of locations for the development of the DP in accordance with the requirements of various stakeholders is performed in this paper, as a prerequisite for the establishment of an ecological, economic, and socially sustainable logistics network in the observed area. To solve this problem, a new hybrid model of multi-criteria decision-making (MCDM) that combines Delphi, AHP (Analytical Hierarchy Process), and CODAS (Combinative Distance-based Assessment) methods in a grey environment is developed. The main contributions of this paper are the defined model, the problem-solving approach based on finding a compromise solution, simultaneous consideration of the environmental, economic, and social sustainability of the DP concept and its implementation in the regional international markets. The applicability of the approach and the defined MCDM model is demonstrated by solving a real-life case study of ranking the potential DP locations in the Western Balkans region. Based on the obtained results, it is concluded that in the current market conditions, it would be most realistic to open three DP terminals, in Zagreb, Ljubljana, and Belgrade.


2014 ◽  
Vol 564 ◽  
pp. 740-746 ◽  
Author(s):  
Abdolhossein Sadrnia ◽  
N. Ismail ◽  
M.K.A.M. Ariffin ◽  
Zulkifli Norzima ◽  
Omid Boyer

The shortage of material and environmental legislations have encouraged car manufacturers to recycle used material in end of life vehicles (ELVs), reverse logistics are essential to the concerns of the automotive supply chain. In this research, a profit model multi-echelon reverse logistics network including collection center, shredder center and recycling center is developed to recycle automotive parts. The work was continued by illustrating empirical application in wiring harness manufacturer that would like to recycle wire harnesses and extract copper. With regards to the complexity of the reverse logistics network, traditional method cannot be implemented for solving them. Thus, an evolutionary algorithm based genetic algorithm (GA) is applied as a solution methodology to solve mixed integer linear programming model and find the optimum solution. The results emphasize the efficiency of the modeling and solving method so that in the case study the company gained more than 27 thousand dollars through the establishment of reverse logistics for recycling copper.


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