A simultaneous facility location, vehicle routing and dynamic pricing in a distribution network

In this paper we consider the location-routing problem which combines the facility location and the vehicle routing decisions. In this type of problem, we have to determine the location of facilities within a set of possible locations and routes of the vehicles to meet the demands of number of customers. Since the location-routing problem is NP-hard, it is difficult to obtain optimal solution within a reasonable computational time. Therefore, a two-phase ant colony optimization algorithm is developed which solves facility location problem and vehicle routing problem hierarchically. Its performance is examined through a comparative study. The experimental results show that the proposed ant colony optimization algorithm can be a viable solution method for the general transportation network planning.

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A Nonlinear Integer Programming Model for Integrated Location, Inventory, and Routing Decisions in a Closed-Loop Supply Chain

Complexity ◽

10.1155/2018/2726070 ◽

2018 ◽

Vol 2018 ◽

pp. 1-17 ◽

Cited By ~ 9

Author(s):

Hao Guo ◽

Congdong Li ◽

Ying Zhang ◽

Chunnan Zhang ◽

Yu Wang

Keyword(s):

Supply Chain ◽

Integer Programming ◽

Facility Location ◽

Vehicle Routing ◽

Closed Loop ◽

Programming Model ◽

Nonlinear Integer Programming ◽

Inventory Routing ◽

Closed Loop Supply Chain ◽

Integer Programming Model

Facility location, inventory management, and vehicle routing are three important decisions in supply chain management, and location-inventory-routing problems consider them jointly to improve the performance and efficiency of today’s supply chain networks. In this paper, we study a location-inventory-routing problem to minimize the total cost in a closed-loop supply chain that has forward and reverse logistics flows. First, we formulate this problem as a nonlinear integer programming model to optimize facility location, inventory control, and vehicle routing decisions simultaneously in such a system. Second, we develop a novel heuristic approach that incorporates simulated annealing into adaptive genetic algorithm to solve the model efficiently. Last, numerical analysis is presented to validate our solution approach, and it also provides meaningful managerial insight into how to improve the closed-loop supply chain under study.

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Electric vehicle routing problem with backhauls considering the location of charging stations and the operation of the electric power distribution system

TecnoLógicas ◽

10.22430/22565337.1186 ◽

2019 ◽

Vol 22 (44) ◽

pp. 1-20 ◽

Cited By ~ 1

Author(s):

Luis Carlos Cubides ◽

Andrés Arias Londoño ◽

Mauricio Granada Echeverri

Keyword(s):

Vehicle Routing ◽

Electric Vehicle ◽

Power Distribution ◽

Vehicle Routing Problem ◽

Distribution Network ◽

Optimal Operation ◽

Mixed Integer ◽

Routing Problem ◽

Battery Capacity ◽

Charging Stations

Logistics companies are largely encouraged to make greener their operations through an efficient solution with electric vehicles (EVs). However, the driving range is one of the limiting aspects for the introduction of EVs in logistics fleet, due to the low capacity provided by the batteries to perform the routes. In this regards, it is necessary to set up a framework to virtually increase this battery capacity by locating EV charging stations (EVCSs) along the transportation network for the completion of their routes. By the other side, the Distribution Network Operators (DNOs) express the concern associated with the inclusion of new power demands to be attended (installation of EVCSs) in the Distribution Network (DN), without reducing the optimal power supply management for the end-users. Under these circumstances, in this paper the Electric Vehicle Routing Problem with Backhauls and optimal operation of the Distribution Network (EVRPB-DN) is introduced and formulated as a mixed-integer linear programming model, considering the operation of the DN in conditions of maximum power demand. Different candidate points for the EVs charging are considered to recharge the battery at the end of the linehaul route or during the backhaul route. The problem is formulated as a multi-objective approach where the transportation and power distribution networks operation are modeled. The performance and effectiveness of the proposed formulation is tested in VRPB instance datasets and DN test systems from the literature. Pareto fronts for each instance are presented, using the ε-constraint methodology.

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