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RESTRUCTURING PARCEL DELIVERY NETWORK BY CONSIDERING DYNAMIC CUSTOMER DEMAND


Business Administration and Management

RESTRUCTURING PARCEL DELIVERY NETWORK BY CONSIDERING DYNAMIC CUSTOMER DEMAND

Name and surname of author:

Hyun-Woong Jin

Year:
2018
Volume:
21
Issue:
2
Keywords:
Parcel delivery service, network design, meta-heuristics, GRASP
DOI (& full text):
Anotation:
Parcel delivery service is one of the fastest growing industries in the world as the e-commerce such as online shopping mall expands rapidly. To increase its market share, most of parcel delivery…more
Parcel delivery service is one of the fastest growing industries in the world as the e-commerce such as online shopping mall expands rapidly. To increase its market share, most of parcel delivery service companies construct their delivery network as a form of hub-spoke network which is known to be efficient to deliver large scale products through widely spread area. In hub-spoke network, the number of hubs and their locations are important decision issues. Even though there are many researches on the hub-spoke network design, there is a lack of researches which deal with the fluctuating customer demand. Moreover, all the previous researches considering the fluctuating customer demand assumed that the capacity of hub facility is unlimited. Therefore, this research aims to propose the restructuring procedure of the parcel delivery network by considering the fluctuating customer demand with the capacitated hub facilities. In this research, utilization of temporary hubs is proposed so as to satisfy the fluctuating customer demand. Temporary hub responds to the excessive demands assigned to the permanent hubs and it is closed during the recession period to reduce its operating cost. A nonlinear integer programming model is constructed to decide the number of temporary hubs and their location at each time period. Since the complexity of the constructed mathematical model is NP-hard, GRASP based heuristic solution procedure is proposed. To evaluate the appropriateness of the proposed algorithm, experimental test with various demand sets considering four design factors are performed and the performance of the proposed algorithm is compared with the existing meta-heuristic algorithm. Test results show that the algorithm proposed in this research is more robust than the existing algorithm against the fluctuation of customer demand as well as it provides overall better results.
Section:
Business Administration and Management

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