Variable Neighborhood Search heuristic for the Inventory Routing Problem in fuel delivery

2012 ◽  
Vol 39 (18) ◽  
pp. 13390-13398 ◽  
Author(s):  
Dražen Popović ◽  
Milorad Vidović ◽  
Gordana Radivojević
Keyword(s):  
Variable Neighborhood Search ◽  
Neighborhood Search ◽  
Inventory Routing ◽  
Routing Problem ◽  
Search Heuristic ◽  
Inventory Routing Problem ◽  
Fuel Delivery

scholarly journals A Memetic Algorithm for the Inventory Routing Problem

2021 ◽  
Author(s):  
Mohame Salim Amri Sakhri ◽  
Mounira Tlili ◽  
Ouajdi Korbaa
Keyword(s):  
Supply Chain ◽  
Variable Neighborhood Search ◽  
Memetic Algorithm ◽  
Population Based ◽  
Single Type ◽  
Neighborhood Search ◽  
Inventory Routing ◽  
Routing Problem ◽  
Inventory Routing Problem ◽  
Single Vehicle

Abstract In this paper, we investigated an Inventory Routing Problem (IRP) with deterministic customer demand, in a two-tiered supply chain. The supply chain network consists of a supplier who uses a single vehicle with a given capacity to deliver a single type of product to many customers. We are interested in population-based algorithms to solve our problem. A Memetic Algorithm (MA) is developed based on Genetic Algorithm (GA) and Variable Neighborhood Search methods (VNS). The proposed metaheuristics are tested on small and large sizes referenced benchmarks. The results of MA are compared with those of classical GA and with the optimal solutions from the literature. The comparison showed the efficiency of the MA use and its ability to generate high quality solutions within a reasonable time.

scholarly journals ADAPTATION OF THE VARIABLE NEIGHBORHOOD SEARCH HEURISTIC TO SOLVE THE VEHICLE ROUTING PROBLEM

2012 ◽  
Vol 12 (1) ◽  
pp. 10 ◽  
Author(s):  
ARIF IMRAN ◽  
LIANE OKDINAWATI
Keyword(s):  
Vehicle Routing ◽  
Vehicle Routing Problem ◽  
Variable Neighborhood Search ◽  
Initial Solution ◽  
Neighborhood Search ◽  
Search Methods ◽  
Routing Problem ◽  
Search Heuristic ◽  
Dijkstra's Algorithm ◽  
Sweep Algorithm

The vehicle routing problem is investigated by using some adaptations of the variable neighborhood search (VNS).The initial solution was obtained by Dijkstra’s algorithm based on cost network constructed by the sweep algorithm andthe 2-opt. Our VNS algorithm use several neighborhoods which were adapted for this problem. In addition, a number oflocal search methods together with a diversification procedure were used. The algorithm was then tested on the data setsfrom the literature and it produced competitive results if compared to the solutions published.

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