Journal
TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
Volume 143, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.tre.2020.102118
Keywords
Location-routing problem; State-space-time network; Synchronization degree; Lagrangian relaxation model; Clarke-Wright
Categories
Funding
- National Natural Science Foundation of China [71871035, 71831008, 71671107]
- Humanity and Social Science Youth Foundation of Ministry of Education of China [18YJC630189]
- Key Science and Technology Research Project of Chongqing Municipal Education Commission [KJZD-K202000702]
- Social Science Planning Foundation of Chongqing of China [2019YBGL054]
- Key Project of Human Social Science of Chongqing Municipal Education Commission [20SKGH079]
- 2018 Chongqing Liuchuang Plan Innovation Project [cx2018111]
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Optimization of the green logistics location-routing problem with eco-packages involves solving a two-echelon location-routing problem and the pickup and delivery problem with time windows. The first echelon consists of large eco-package transport, which is modeled by a time-discretized transport-concentrated network flow programming in the resource sharing state-space-time (SST) network. The second echelon focuses on small eco-package pickups and deliveries, established by the cost-minimized synchronization-oriented location routing model that minimizes the total generalized cost, which includes internal transportation cost, value of eco-packages, short-term benefits and environmental externalities. In addition, the Gaussian mixture clustering algorithm is utilized to assign customers to their respective service providers in the pickup and delivery process, and a Clarke-Wright saving method-based non-dominated sorting genetic algorithm II is designed to optimize pickup and delivery routes, and improve their cost-effectiveness and degree of synchronization. Different strategy testing results are used in the service phase as input data to calculate the cost of the transport phase, which is solved through a Lagrangian relaxation approach. The 3D SST network representation innovatively captures the eco-package route sequence and state transition constraints over the shortest path in the pickup and delivery at any given moment of the transport phase. A large-scale logistics network in Chengdu, China, is used to demonstrate the proposed model and algorithm, and undertake sensitivity analysis considering the life cycle of green eco-packages.
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