scholarly journals The Model for Location Routing Problem with Roaming Delivery Locations

2020 ◽  
Vol 21 (2) ◽  
pp. 174-184
Author(s):  
Stefanus Ivan Laksono ◽  
Y. M. Kinley Aritonang ◽  
Julius Dharma Lesmono
Keyword(s):  
Purchase Decision ◽  
Global Competition ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing ◽  
Last Mile ◽  
The World ◽  
Direct Delivery ◽  
Fuel Costs ◽  
Distribution Efficiency

The Location Routing Problem with Roaming Delivery Locations (LRPRDL) is a model that represents company activities in delivering products to final customers. Direct delivery to final customers has increased significantly over the growth of e-commerce in the world. E-commerce or business-to-customer companies are urged to increase their last-mile distribution efficiency to survive in the global competition. For that purpose, the LRPRDL  model was proposed to increase the efficiency of the company’s last-mile distribution. The model aims to minimize the sum of open depots and transportation costs by determining the number and location of depots and the shipping routes. The LRPRDL was implemented in an instance with four depot candidates, 15 customers, and six vehicles. The instance was solved to the optimality by using a public solver Gurobi. Furthermore, this research conducted a sensitivity analysis on the open depots and fuel costs, customer demand, and radius. The study indicated that customer’s demand and radius have a significant impact on the purchase decision.

scholarly journals POPMUSIC for the world location-routing problem

2013 ◽  
Vol 2 (3) ◽  
pp. 231-254 ◽  
Author(s):  
Adriana C. F. Alvim ◽  
Éric D. Taillard
Keyword(s):  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing ◽  
The World

scholarly journals Routing optimization of the emergency supplies distribution vehicles using NSGA-II algorithm: a case study

2020 ◽  
Vol 325 ◽  
pp. 03002
Author(s):  
Xingjiang Li ◽  
Hanyun Yin ◽  
Fuhai Yan
Keyword(s):  
Programming Model ◽  
Actual Situation ◽  
Intensive Study ◽  
Nsga Ii ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Routing Optimization ◽  
Location Routing ◽  
The World

In recent years, emergencies, including natural disasters and other public disasters, have seriously threatened the lives and property security of people all over the world. In order to save more people’s lives and reduce the losses caused by disasters, many researchers have carried out intensive study on the distribution of emergency supplies. This paper first studies Location-Routing Problem(LRP) of alternative logistics centers and material demand points, and constructs a multi-objective integer programming model based on the actual situation. The model consists of two objectives: (1) the minimum total transportation time; (2) the maximum total emergency material satisfaction. Then an algorithm is introduced to solve the above model: NSGA-II. Finally, the emergency materials distribution in Hubei Province is taken as an example to verify the applicability and effectiveness of the above method and the models.

Fuzzy multi-objective location and routing problem

2020 ◽  
Vol 39 (3) ◽  
pp. 3259-3273
Author(s):  
Nasser Shahsavari-Pour ◽  
Najmeh Bahram-Pour ◽  
Mojde Kazemi
Keyword(s):  
Firefly Algorithm ◽  
High Reliability ◽  
Research Area ◽  
Nsga Ii ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Allocation ◽  
Multi Objective ◽  
Location Routing ◽  
The Cost

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.

scholarly journals Combining Heuristics with Simulation and Fuzzy Logic to Solve a Flexible-Size Location Routing Problem under Uncertainty

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 ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Local Search ◽  
Vehicle Routing Problem ◽  
Large Scale ◽  
Iterated Local Search ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing ◽  
Fuzzy Pattern ◽  
Reasonable Computing

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.

Multiobjective location-routing problem of relief commodities with reliability

2021 ◽  
Author(s):  
Hossein Beiki ◽  
Seyed M. Seyedhosseini ◽  
Leonardus W. W. Mihardjo ◽  
Seyed M. Seyedaliakbar
Keyword(s):  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing
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