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.

An Iterated Local Search for Solving A Location-Routing Problem

2010 ◽  
Vol 36 ◽  
pp. 875-882 ◽  
Author(s):  
Houda Derbel ◽  
Bassem Jarboui ◽  
Said Hanafi ◽  
Habib Chabchoub
Keyword(s):  
Local Search ◽  
Iterated Local Search ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing

Genetic algorithm with iterated local search for solving a location-routing problem

2012 ◽  
Vol 39 (3) ◽  
pp. 2865-2871 ◽  
Author(s):  
Houda Derbel ◽  
Bassem Jarboui ◽  
Saïd Hanafi ◽  
Habib Chabchoub
Keyword(s):  
Genetic Algorithm ◽  
Local Search ◽  
Iterated Local Search ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Location Routing

Solving a multi-objective multi-depot stochastic location-routing problem by a hybrid simulated annealing algorithm

2009 ◽  
Vol 223 (8) ◽  
pp. 1045-1054 ◽  
Author(s):  
H A Hassan-Pour ◽  
M Mosadegh-Khah ◽  
R Tavakkoli-Moghaddam
Keyword(s):  
Simulated Annealing ◽  
Large Scale ◽  
Simulated Annealing Algorithm ◽  
Genetic Operators ◽  
Location Routing Problem ◽  
Routing Problem ◽  
Multi Objective ◽  
Location Routing ◽  
Proposed Model ◽  
Stochastic Location

This paper presents a novel mathematical model for a stochastic location-routing problem (SLRP) that minimizes the facilities establishing cost and transportation cost, and maximizes the probability of delivery to customers. In this proposed model, new aspects of a location-routing problem (LRP), such as stochastic availability of facilities and routes, are developed that are similar to real-word problems. The proposed model is solved in two stages: (i) solving the facility location problem (FLP) by a mathematical algorithm and (ii) solving the multi-objective multi-depot vehicle routing problem (MO-MDVRP) by a simulated annealing (SA) algorithm hybridized by genetic operators, namely mutation and crossover. The proposed SA can find good solutions in a reasonable time. It solves the proposed model in large-scale problems with acceptable results. Finally, a trade-off curve is used to depict and discuss a large-sized problem. The associated results are compared with the results obtained by the lower bound and Lingo 8.0 software.

scholarly journals An iterated local search algorithm for the vehicle routing problem with convex time penalty functions

2008 ◽  
Vol 156 (11) ◽  
pp. 2050-2069 ◽  
Author(s):  
Toshihide Ibaraki ◽  
Shinji Imahori ◽  
Koji Nonobe ◽  
Kensuke Sobue ◽  
Takeaki Uno ◽  
...  
Keyword(s):  
Local Search ◽  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Search Algorithm ◽  
Iterated Local Search ◽  
Penalty Functions ◽  
Local Search Algorithm ◽  
Routing Problem
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