Multi-product pickup and delivery supply chain design with location-routing and direct shipment

Azizi, Vahid

doi:10.1016/j.ijpe.2020.107648

Cited by 33 publications

(15 citation statements)

References 17 publications

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“…For these types of problems, metaheuristic methods perform well as a portion of the solution space is searched heuristically with near optimal solution. Population-based evolutionary algorithms are now widely used for solving engineering, business and supply chain optimization problems (Kumar and Chatterjee, 2013;Ahmadizar et al 2015;He at al., 2015;Musavi & Bozorgi-Amiri, 2017;Pariazar & Sir, 2018;Azizi & Hu, 2020). To validate the results and evaluate the performance of the model, meta-heuristics GA is utilized to solve the test problem.…”

Section: Genetic Algorithm For the Optimizationmentioning

confidence: 99%

Optimal supply chain design with product family: A cloud-based framework with real-time data consideration

Ali

Alkilabi

et al. 2021

Computers & Operations Research

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Section: Genetic Algorithm For the Optimizationmentioning

confidence: 99%

Optimal supply chain design with product family: A cloud-based framework with real-time data consideration

Ali

Alkilabi

et al. 2021

Computers & Operations Research

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“…Ahmadizar et al [29] presented a model that considers two-level vehicle routing together with cross-docking and developed a hybrid genetic algorithm for the problem. Azizi and Hu [30] presented a decision model considering the distribution centre location, the routes of the pickup and delivery vehicles, and direct transportation and performed effective computational experiments.…”

Section: Vehicle Routing Problemmentioning

confidence: 99%

“…The value 𝛾 was considered as maximum delay time allowed for delivery. We set γ to vary in [0,30]. The optimized distribution routes and the number of logistics vehicles with different value γ were tested in Figure 10.…”

Section: Impacts Of Equity Patternsmentioning

confidence: 99%

Equity‐oriented vehicle routing optimization for catering distribution services with timeliness requirements

Wang

Yang

Yao

et al. 2021

IET Intelligent Trans Sys

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The rapid development in the catering services and urban logistics industries has significantly promoted the prosperity of business-to-consumer (B2C) e-commerce urban logistics distribution, which is gaining increasing interest from food producers, distribution platforms, and consumers. Unlike traditional logistics supply chains, catering distribution services have strong timeliness and consideration of delivery delay. Traditional distribution platforms usually group commodities by their origins or destinations and then transport each group with one logistics vehicle. However, for a logistics distribution area with limited commodities, the vehicle capacity cannot be fully utilized if one vehicle can only transport commodities with the same origin or destination. Therefore, a mixed-load strategy is proposed in which commodities with different origins or destinations in a distribution area could be transported by the same vehicle to improve vehicle capacity utilization. A mixed-load strategy would further cause delivery sequencing problems, leading to different delivery delays for customers. This study proposed an equity-oriented vehicle routing problem for food distribution services with timeliness requirements considering a mixed-loading strategy and vehicle capacity constraints. For the above problem, a multi-commodity flow optimization model was constructed for the equity-oriented vehicle routing problem and a mixed-load strategy based on a time-discretized space-time-state network representation. An augmented Lagrangian relaxation approach was utilized to reformulate the original model and thus effectively solve the proposed model. Furthermore, the augmented Lagrangian model was decomposed and linearized into a series of shortest path searching subproblems and iteratively solved by a dynamic programming algorithm using an alternating direction method of multipliers (ADMM)-based solution framework. Finally, the proposed model and solution approaches were tested on numerous networks.

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“…e more integrated these problems are, the more efficient a routing system can be. e problem addressed in our paper is similar to Azizi and Hu [4] and Baniasadi et al [5]. Unlike Azizi and Hu [4], we consider SPD among lockers and customers.…”

Section: Introductionmentioning

confidence: 99%

“…e problem addressed in our paper is similar to Azizi and Hu [4] and Baniasadi et al [5]. Unlike Azizi and Hu [4], we consider SPD among lockers and customers. Our motivation is to design a distribution network that allows a courier to pickup and deliver more parcels by making fewer trips, a move aimed at lowering labor cost and boosting revenue.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous Pickup and Delivery Traveling Salesman Problem considering the Express Lockers Using Attention Route Planning Network

et al. 2021

Computational Intelligence and Neuroscience

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This paper presents a simultaneous pickup and delivery route designing model, which considers the use of express lockers. Unlike the traditional traveling salesman problem (TSP), this model analyzes the scenario that a courier serves a neighborhood with multiple trips. Considering the locker and vehicle capacity, the total cost is constituted of back order, lost sale, and traveling time. We aim to minimize the total cost when satisfying all requests. A modified deep Q-learning network is designed to get the optimal results from our model, leveraging masked multi-head attention to select the courier paths. Our algorithm outperforms other stochastic optimization methods with better optimal solutions and O(n) computational time in evaluation processes. The experiment has shown that reinforcement learning is a better choice than traditional stochastic optimization methods, consuming less power and time during evaluation processes, which indicates that this approach fits better for large-scale data and broad deployment.

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Multi-product pickup and delivery supply chain design with location-routing and direct shipment

Cited by 33 publications

References 17 publications

Optimal supply chain design with product family: A cloud-based framework with real-time data consideration

Optimal supply chain design with product family: A cloud-based framework with real-time data consideration

Equity‐oriented vehicle routing optimization for catering distribution services with timeliness requirements

Simultaneous Pickup and Delivery Traveling Salesman Problem considering the Express Lockers Using Attention Route Planning Network

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