Hub-and-spoke network design under operational and disruption risks

Zhalechian, Mohammad; Torabi, S. Ali; Mohammadi, Mehrdad

doi:10.1016/j.tre.2017.11.001

Cited by 79 publications

(37 citation statements)

References 46 publications

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“…The concept of supply chain resilience gained prominent importance during recent years in supply chain risk management research [35]. Supply chain resilience is a relatively new concept to mitigate risks that can be defined as the ability to reduce the probability of a disruption, to reduce the impact of disruption, and to reduce the recovery time to normal performance [36].…”

Section: Literature Reviewmentioning

confidence: 99%

Interactive Fuzzy Multi Criteria Decision Making Approach for Supplier Selection and Order Allocation in a Resilient Supply Chain

et al. 2019

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Modern supply chains are vulnerable to high impact, low probability disruption risks. A supply chain usually operates in such a network of entities where the resilience of one supplier is critical to overall supply chain resilience. Therefore, resilient planning is a key strategic requirement in supplier selection decisions for a competitive supply chain. The aim of this research is to develop quantitative resilient criteria for supplier selection and order allocation in a fuzzy environment. To serve the purpose, a possibilistic fuzzy multi-objective approach was proposed and an interactive fuzzy optimization solution methodology was developed. Using the proposed approach, organizations can tradeoff between cost and resilience in supply networks. The approach is illustrated using a supply chain case from a garments manufacturing company.

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Section: Literature Reviewmentioning

confidence: 99%

Interactive Fuzzy Multi Criteria Decision Making Approach for Supplier Selection and Order Allocation in a Resilient Supply Chain

et al. 2019

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“…Interested readers can refer to Pishvaee and Torabi (2010), Rabbani et al (2018) and Zhalechian et al (2018) for further explanations. Finally, the auxiliary crisp model counterpart can be formulated as:…”

Section: Equivalent Auxiliary Crisp Modelmentioning

confidence: 99%

A new bi-objective model of the urban public transportation hub network design under uncertainty

et al. 2019

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This paper presents a new bi-objective multi-modal hub location problem with multiple assignment and capacity considerations for the design of an urban public transportation network under uncertainty. Because of the high construction costs of hub links in an urban public transportation network, it is not economic to create a complete hub network. Moreover, the demand is assumed to be dependent on the utility proposed by each hub. Thus, the elasticity of the demand is considered in this paper. The presented model also has the ability to compute the number of each type of transportation vehicles between every two hubs. The objectives of this model are to maximize the benefits of transportation by establishing hub facilities and to minimize the total transportation time. Since exact values of some parameters are not known in advance, a fuzzy multi-objective programming based approach is proposed to optimally solve small-sized problems. For medium and large-sized problems, a meta-heuristic algorithm, namely multi-objective particle swarm optimization is applied and its performance is compared with results from the non-dominated sorting genetic algorithm. Our experimental results demonstrated the validity of our developed model and approaches. Moreover, an intensive sensitivity analyze study is carried out on a real-case application related to the monorail project of the holy city of Qom.

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“…Zhalechian et al proposed a novel scenario-based model to design a resilient hub network and presented an objective function to calculate the hub network resilience. They further presented a hybrid evolutionary algorithm to solve the model for large-scale problems [33]. Moghal et al developed a mixed-integer linear programming model for minimizing transportation costs and inventory of food grains in India, and also used a chemical reaction optimization (CRO) algorithm for testing the model, ending up indicating superior computational performance of the model, as compared to similar meta-heuristic algorithms [34].…”

Section: Hybrid Metaheuristic Literaturementioning

confidence: 99%

A P-hub median network design problem with preventive reliability approach for before and after hub failure

Eydi

Nasiri

2019

Sādhanā

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Hubs are vital elements of communication and transportation networks and play an important role in interchanging the flows of information/passenger/goods. For this purpose, designing a highly reliable hub network is very critical, because inefficiency of even a single hub across the network tends to reduce the efficiency of the whole network in transferring the flow appropriately. In this research, a bi-objective mathematical model was designed to study the situations before and after hub failure. Considering reliability, the first objective was to maximize the flow through the network, and the second objective was to prevent wasting the flow due to a possible hub failure. The lexicographic method was used to solve this multi-objective problem with dependent objectives. This method represents an appropriate solution for problems whose objective functions are of different priorities or depend on one another. Various cases of different sizes were used to evaluate the model in terms of reliability. Since the hub location problem is an NP-Hard problem of commonly large dimensions, a hybrid meta-heuristic algorithm called ''memetic algorithm'' was used to have it solved. The algorithm was a combination of genetic algorithm with simulated annealing algorithm, where simulated annealing algorithm was used for local neighborhood search. Findings indicated that, consideration of the backup hub tends to enhance route reliability, thereby increasing the flow through the network, as compared to the case with no backup hub.

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Hub-and-spoke network design under operational and disruption risks

Cited by 79 publications

References 46 publications

Interactive Fuzzy Multi Criteria Decision Making Approach for Supplier Selection and Order Allocation in a Resilient Supply Chain

Interactive Fuzzy Multi Criteria Decision Making Approach for Supplier Selection and Order Allocation in a Resilient Supply Chain

A new bi-objective model of the urban public transportation hub network design under uncertainty

A P-hub median network design problem with preventive reliability approach for before and after hub failure

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