pickup and delivery
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Author(s):  
Yan Sun ◽  
Nan Yu ◽  
Baoliang Huang

AbstractThis paper addresses the multi-objective optimization for the road–rail intermodal routing problem that aims to minimize the total costs and carbon dioxide emissions of the routes. To achieve high timeliness of the entire transportation process, pickup and delivery services are simultaneously improved based on the employment of fuzzy soft time windows to measure their service levels. The modeling of road–rail intermodal routing considers fixed schedules of rail and time flexibility of road to match the real-world transportation scenario, in which travel times and carbon dioxide emission factors of road services are considered to be time-varying. To improve the feasibility of the routing, uncertainty of travel times and carbon dioxide emission factors of road services and capacities of rail services are incorporated into the problem. By applying trapezoidal fuzzy numbers to formulate the uncertainty, we propose a fuzzy multi-objective nonlinear optimization model for the routing problem that integrates the truck departure time planning for road services. After processing the model with fuzzy chance-constrained programming and linearization, we obtain an auxiliary equivalent crisp linear model and solve it by designing an interactive fuzzy programming approach with the Bounded Objective Function method. Based on an empirical case study, we demonstrate the validity of the proposed approach and discuss the effects of improving the confidence levels and service levels on the optimization results. The case analysis reveals several managerial insights that help to realize an efficient transportation organization by making effective trade-offs among lowering costs, reducing emissions, improving service levels, and enhancing feasibility.


2021 ◽  
Author(s):  
Hang Zhou ◽  
Hu Qin ◽  
Zizhen Zhang ◽  
Jiliu Li

Abstract In this paper, we propose a tabu search algorithm for the two-echelon vehicle routing problem with time windows and simultaneous pickup and delivery (2E-VRPTWSPD), which is a new variant of the two-echelon vehicle routing problem (2E-VRP) by considering the time windows constraints and simultaneous pickup and delivery. In 2EVRPTWSPD, the pickup and delivery activities are performed simultaneously by the same vehicles through the depot to satellites in the first echelon and satellites to customers in the second echelon, where each customer has a specified time window. To solve this problem, firstly, we formulate the problem with a mathematical model. Then, we implement a variable neighborhood tabu search algorithm with the proposed solution representation of dummy satellites to solve large-scale instances. Dummy satellites time windows are used in our algorithm to speed up the algorithm. Finally, we generate two instance sets based on the existing 2E-VRP and 2E-VRPTW benchmark sets and conduct additional experiments to analyze the performance of our algorithm.


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