A Recent Brief Survey for the Multi Depot Heterogenous Vehicle Routing Problem with Time Windows

Rabbouch, Bochra; Mraïhi, Rafaa; Saâdaoui, Foued

doi:10.1007/978-3-319-76351-4_15

Cited by 9 publications

(3 citation statements)

References 43 publications

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“…e Shapley value method is utilized in this study. Here, A and A s are defined as the grand alliance consisting of all logistics facilities in the 2E-CMDPDTW and a suballiance including some of them, (2) Set system parameters: pop size , tmax, rmax (3) Set genetic parameters: p cro , p mut Implement (4) for run � 1: rmax (5) Generate the initial population by greedy algorithm and scanning algorithm (6) for i � 1: tmax (7) for i � 1: pop size (8) Evaluate the objective function ( 9) End (10) Carry out order crossover and polynomial mutation for the population (11) Generate the offspring population Q i (12) Combine the parent population P i and the offspring population Q i to generate a new population R i (13) Perform the non-dominated sorting and crowding distance calculating for the R i (14) Select individuals from the R i to generate a new population P i+1 (15) end ( 16) end (17) Obtain the optimal solutions ALGORITHM 2: Procedure of the proposed Im-NSGA-II.…”

Section: Shapley Value Methodmentioning

confidence: 99%

“…e MDVRPTW and its derivatives have received much attention both in the theoretical and practical fields. For example, Rabbouch et al [11] reviewed the relevant literature concerning the MDVRPTW and proved that the satisfaction of time windows is important and necessary.…”

Section: Mdvrptwmentioning

confidence: 99%

“…Constraints ( 9) and (10) guarantee that each DC and PC only can be served by one semitrailer truck, respectively. Constraint (11) eliminates subtours of every route in the first echelon. Constraints (12) and (13) express that the demands of each DC and PC can be satisfied, respectively.…”

Section: 31mentioning

confidence: 99%

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Two-Echelon Multidepot Logistics Network Design with Resource Sharing

Luo

Wang

Tang

et al. 2021

Journal of Advanced Transportation

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Resource sharing within a logistics network offers an effective way to solve problems resulting from inefficient and costly operations of individual logistics facilities. However, the existing analysis of resource sharing and profit allocation is still limited. Therefore, this study aims to model resource sharing in two-echelon delivery and pickup logistics networks to improve the overall efficiency and decrease the total network operating cost. A bi-objective integer programming model is first proposed for two-echelon collaborative multidepot pickup and delivery problems with time windows (2E-CMDPDTW) to seek the minimization of operating costs and number of vehicles. Integrating a customer clustering algorithm, a greedy algorithm, and an improved nondominated sorting genetic algorithm-II (Im-NSGA-II), a hybrid method is then designed to handle the 2E-CMDPDTW model. The customer clustering and the greedy algorithms are employed to generate locally optimized initial solutions to accelerate the calculating velocity and guarantee the diversity of feasible solutions. The Im-NSGA-II combines the order crossover operation and the polynomial mutation process to find the optimal solution of the 2E-CMDPDTW. The comparative results show that the proposed hybrid method outperforms the NSGA-II and the multiobjective genetic algorithm. Furthermore, a Shapley value method is used for allocating total profits of established alliances and finding an optimal coalition sequence of the logistics facilities joining alliances based on the strictly monotonic path strategy. Finally, a case study of 2E-CMDPDTW in Chongqing China is conducted to validate the feasibility. Results indicate that this study contributes to long-term partnerships between logistics facilities within multi-echelon logistics networks in practice and contributes to the long-term sustainability of urban logistics pickup and delivery networks’ development.

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