A math-heuristic for the warehouse location–routing problem in disaster relief

2014 ◽  
Vol 42 ◽  
pp. 25-39 ◽  
Author(s):  
Stefan Rath ◽  
Walter J. Gutjahr
2020 ◽  
Vol 147 ◽  
pp. 106632
Author(s):  
Xiaowen Wei ◽  
Huaxin Qiu ◽  
Dujuan Wang ◽  
Jiahui Duan ◽  
Yanzhang Wang ◽  
...  

1994 ◽  
Vol 76 (1) ◽  
pp. 111-127 ◽  
Author(s):  
P.H. Hansen ◽  
B. Hegedahl ◽  
S. Hjortkjær ◽  
B. Obel

2020 ◽  
Vol 39 (3) ◽  
pp. 3259-3273
Author(s):  
Nasser Shahsavari-Pour ◽  
Najmeh Bahram-Pour ◽  
Mojde Kazemi

The location-routing problem is a research area that simultaneously solves location-allocation and vehicle routing issues. It is critical to delivering emergency goods to customers with high reliability. In this paper, reliability in location and routing problems was considered as the probability of failure in depots, vehicles, and routs. The problem has two objectives, minimizing the cost and maximizing the reliability, the latter expressed by minimizing the expected cost of failure. First, a mathematical model of the problem was presented and due to its NP-hard nature, it was solved by a meta-heuristic approach using a NSGA-II algorithm and a discrete multi-objective firefly algorithm. The efficiency of these algorithms was studied through a complete set of examples and it was found that the multi-objective discrete firefly algorithm has a better Diversification Metric (DM) index; the Mean Ideal Distance (MID) and Spacing Metric (SM) indexes are only suitable for small to medium problems, losing their effectiveness for big problems.


Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 45
Author(s):  
Rafael D. Tordecilla ◽  
Pedro J. Copado-Méndez ◽  
Javier Panadero ◽  
Carlos L. Quintero-Araujo ◽  
Jairo R. Montoya-Torres ◽  
...  

The location routing problem integrates both a facility location and a vehicle routing problem. Each of these problems are NP-hard in nature, which justifies the use of heuristic-based algorithms when dealing with large-scale instances that need to be solved in reasonable computing times. This paper discusses a realistic variant of the problem that considers facilities of different sizes and two types of uncertainty conditions. In particular, we assume that some customers’ demands are stochastic, while others follow a fuzzy pattern. An iterated local search metaheuristic is integrated with simulation and fuzzy logic to solve the aforementioned problem, and a series of computational experiments are run to illustrate the potential of the proposed algorithm.


Author(s):  
Hossein Beiki ◽  
Seyed M. Seyedhosseini ◽  
Leonardus W. W. Mihardjo ◽  
Seyed M. Seyedaliakbar

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