A multiple-depot, multiple-vehicle, location-routing problem with stochastically processed demands
Computers and Operations Research
Heuristic solutions to multi-depot location-routing problems
Computers and Operations Research
A location-routing-loading problem for bill delivery services
Computers and Industrial Engineering - Supply chain management
A compact model and tight bounds for a combined location-routing problem
Computers and Operations Research
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
A memetic algorithm with population management (MA|PM) for the capacitated location-routing problem
EvoCOP'06 Proceedings of the 6th European conference on Evolutionary Computation in Combinatorial Optimization
Multi-start heuristics for the two-echelon vehicle routing problem
EvoCOP'11 Proceedings of the 11th European conference on Evolutionary computation in combinatorial optimization
Genetic algorithm with iterated local search for solving a location-routing problem
Expert Systems with Applications: An International Journal
Single-Source Capacitated Multi-Facility Weber Problem-An iterative two phase heuristic algorithm
Computers and Operations Research
INFORMS Journal on Computing
A simulated annealing algorithm based approach for balancing and sequencing of mixed-model U-lines
Computers and Industrial Engineering
A GRASP + ILP-based metaheuristic for the capacitated location-routing problem
Journal of Heuristics
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The location routing problem (LRP) is a relatively new research direction within location analysis that takes into account vehicle routing aspects. The goal of LRP is to solve a facility location problem and a vehicle routing problem simultaneously. We propose a simulated annealing (SA) based heuristic for solving the LRP. The proposed SALRP heuristic is tested on three sets of well-known benchmark instances and the results are compared with other heuristics in the literature. The computational study indicates that the proposed SALRP heuristic is competitive with other well-known algorithms.