Risk-averse optimization of disaster relief facility location and vehicle routing under stochastic demand

2020 ◽  
Vol 141 ◽  
pp. 102015 ◽  
Author(s):  
Shaopeng Zhong ◽  
Rong Cheng ◽  
Yu Jiang ◽  
Zhong Wang ◽  
Allan Larsen ◽  
...  
Keyword(s):  
Facility Location ◽  
Vehicle Routing ◽  
Disaster Relief ◽  
Stochastic Demand ◽  
Risk Averse

Facility location models for immobile servers with stochastic demand

2003 ◽  
Vol 51 (1) ◽  
pp. 137-152 ◽  
Author(s):  
Qian Wang ◽  
Rajan Batta ◽  
Christopher M. Rump
Keyword(s):  
Facility Location ◽  
Stochastic Demand ◽  
Location Models ◽  
Facility Location Models

A Two-Phase Meta Heuristic Approach to the Location-Routing Problem for Transportation Network Planning

2013 ◽  
Vol 361-363 ◽  
pp. 1900-1905 ◽  
Author(s):  
Ji Ung Sun
Keyword(s):  
Ant Colony Optimization ◽  
Facility Location ◽  
Vehicle Routing ◽  
Optimization Algorithm ◽  
Transportation Network ◽  
Ant Colony Optimization Algorithm ◽  
Two Phase ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing

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.

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

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
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.

Restocking-Based Rollout Policies for the Vehicle Routing Problem with Stochastic Demand and Duration Limits

2016 ◽  
Vol 50 (2) ◽  
pp. 591-607 ◽  
Author(s):  
Justin C. Goodson ◽  
Barrett W. Thomas ◽  
Jeffrey W. Ohlmann
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Stochastic Demand ◽  
Routing Problem
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